From 83df757cafa9f3a5197a866abe726151b3e252db Mon Sep 17 00:00:00 2001 From: "C. Titus Brown" Date: Sun, 20 Aug 2023 15:15:39 -0700 Subject: [PATCH 01/27] switch to using branchwater via pyo3_branchwater plugin --- benchmarking.snakefile | 40 +++++++++++++++------------------- benchmarks/a_vs_a_1000_t16.txt | 2 +- benchmarks/a_vs_a_1000_t36.txt | 2 -- benchmarks/a_vs_a_1000_t4.txt | 2 +- benchmarks/a_vs_a_1000_t40.txt | 2 -- benchmarks/a_vs_a_1000_t44.txt | 2 -- benchmarks/a_vs_a_1000_t48.txt | 2 -- benchmarks/a_vs_a_1000_t52.txt | 2 -- benchmarks/a_vs_a_1000_t56.txt | 2 -- benchmarks/a_vs_a_1000_t60.txt | 2 -- benchmarks/a_vs_a_1000_t64.txt | 2 -- benchmarks/a_vs_a_1000_t8.txt | 2 +- environment.yml | 11 ++++++++++ 13 files changed, 32 insertions(+), 41 deletions(-) delete mode 100644 benchmarks/a_vs_a_1000_t36.txt delete mode 100644 benchmarks/a_vs_a_1000_t40.txt delete mode 100644 benchmarks/a_vs_a_1000_t44.txt delete mode 100644 benchmarks/a_vs_a_1000_t48.txt delete mode 100644 benchmarks/a_vs_a_1000_t52.txt delete mode 100644 benchmarks/a_vs_a_1000_t56.txt delete mode 100644 benchmarks/a_vs_a_1000_t60.txt delete mode 100644 benchmarks/a_vs_a_1000_t64.txt create mode 100644 environment.yml diff --git a/benchmarking.snakefile b/benchmarking.snakefile index 1b2e560..6de2c2c 100644 --- a/benchmarking.snakefile +++ b/benchmarking.snakefile @@ -1,4 +1,5 @@ -sra_search_bin="/home/ctbrown/scratch/magsearch/bin/searcher" +#sra_search_bin="/home/ctbrown/scratch/magsearch/bin/searcher" +manysearch_cmd = "sourmash scripts manysearch" rule all: input: @@ -10,9 +11,13 @@ rule all: expand("benchmarks/a_vs_a_1000_t{t}.txt", t=[4,8,16]), expand("benchmarks/a_vs_catalog.txt"), +rule threads: + input: + expand("benchmarks/a_vs_a_1000_t{t}.txt", t=[4,8,16]), + + rule a_vs_a: input: - bin=sra_search_bin, queries="data/gtdb-list-a.sigs.txt", against="data/wort-list-a.txt", output: @@ -22,13 +27,12 @@ rule a_vs_a: threads: 32 shell: """ export RAYON_NUM_THREADS={threads} - {input.bin} -k 31 --scaled=1000 -o {output.csv} \ + {manysearch_cmd} -k 31 --scaled=1000 -o {output.csv} \ {input.queries} {input.against} """ rule a_sub_vs_a: input: - bin=sra_search_bin, queries="data/gtdb-list-a-{n}.sigs.txt", against="data/wort-list-a.txt", output: @@ -38,13 +42,12 @@ rule a_sub_vs_a: threads: 32 shell: """ export RAYON_NUM_THREADS={threads} - {input.bin} -k 31 --scaled=1000 -o {output.csv} \ + {manysearch_cmd} -k 31 --scaled=1000 -o {output.csv} \ {input.queries} {input.against} """ rule a_vs_a_sub: input: - bin=sra_search_bin, queries="data/gtdb-list-a.sigs.txt", against="data/wort-list-a-{n}.txt", output: @@ -54,13 +57,12 @@ rule a_vs_a_sub: threads: 32 shell: """ export RAYON_NUM_THREADS={threads} - {input.bin} -k 31 --scaled=1000 -o {output.csv} \ + {manysearch_cmd} -k 31 --scaled=1000 -o {output.csv} \ {input.queries} {input.against} """ rule a_vs_b: input: - bin=sra_search_bin, queries="data/gtdb-list-a.sigs.txt", against="data/wort-list-b.txt", output: @@ -70,13 +72,12 @@ rule a_vs_b: threads: 32 shell: """ export RAYON_NUM_THREADS={threads} - {input.bin} -k 31 --scaled=1000 -o {output.csv} \ + {manysearch_cmd} -k 31 --scaled=1000 -o {output.csv} \ {input.queries} {input.against} """ rule a_vs_c: input: - bin=sra_search_bin, queries="data/gtdb-list-a.sigs.txt", against="data/wort-list-c.txt", output: @@ -86,13 +87,12 @@ rule a_vs_c: threads: 32 shell: """ export RAYON_NUM_THREADS={threads} - {input.bin} -k 31 --scaled=1000 -o {output.csv} \ + {manysearch_cmd} -k 31 --scaled=1000 -o {output.csv} \ {input.queries} {input.against} """ rule a_vs_d: input: - bin=sra_search_bin, queries="data/gtdb-list-a.sigs.txt", against="data/wort-list-d.txt", output: @@ -102,13 +102,12 @@ rule a_vs_d: threads: 32 shell: """ export RAYON_NUM_THREADS={threads} - {input.bin} -k 31 --scaled=1000 -o {output.csv} \ + {manysearch_cmd} -k 31 --scaled=1000 -o {output.csv} \ {input.queries} {input.against} """ rule a_vs_e: input: - bin=sra_search_bin, queries="data/gtdb-list-a.sigs.txt", against="data/wort-list-e.txt", output: @@ -118,13 +117,12 @@ rule a_vs_e: threads: 32 shell: """ export RAYON_NUM_THREADS={threads} - {input.bin} -k 31 --scaled=1000 -o {output.csv} \ + {manysearch_cmd} -k 31 --scaled=1000 -o {output.csv} \ {input.queries} {input.against} """ rule a_vs_largest: input: - bin=sra_search_bin, queries="data/gtdb-list-a.sigs.txt", against="data/wort-largest-10k.txt", output: @@ -134,30 +132,28 @@ rule a_vs_largest: threads: 32 shell: """ export RAYON_NUM_THREADS={threads} - {input.bin} -k 31 --scaled=1000 -o {output.csv} \ + {manysearch_cmd} -k 31 --scaled=1000 -o {output.csv} \ {input.queries} {input.against} """ rule a_vs_a_sub_threads: input: - bin=sra_search_bin, queries="data/gtdb-list-a.sigs.txt", against="data/wort-list-a-{n}.txt", output: csv="outputs/output_a_vs_a_{n}_t{thr}.csv", benchmark: "benchmarks/a_vs_a_{n}_t{thr}.txt" - threads: 64 + threads: 64 # max out threads so nothing else running shell: """ export RAYON_NUM_THREADS={wildcards.thr} - {input.bin} -k 31 --scaled=1000 -o {output.csv} \ + {manysearch_cmd} -k 31 --scaled=1000 -o {output.csv} \ {input.queries} {input.against} """ rule a_vs_catalog: input: - bin=sra_search_bin, queries="data/gtdb-list-a.sigs.txt", against="data/metagenomes-catalog.txt", output: @@ -167,6 +163,6 @@ rule a_vs_catalog: threads: 32 shell: """ export RAYON_NUM_THREADS={threads} - {input.bin} -k 31 --scaled=1000 -o {output.csv} \ + {manysearch_cmd} -k 31 --scaled=1000 -o {output.csv} \ {input.queries} {input.against} || true """ diff --git a/benchmarks/a_vs_a_1000_t16.txt b/benchmarks/a_vs_a_1000_t16.txt index fa2d698..7f416a7 100644 --- a/benchmarks/a_vs_a_1000_t16.txt +++ b/benchmarks/a_vs_a_1000_t16.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -329.2121 0:05:29 6144.40 7038.87 6169.71 6170.21 7404.52 0.10 1137.80 3746.52 +230.3860 0:03:50 5268.45 10198.34 5316.96 5321.81 0.00 6.98 1179.52 2721.43 diff --git a/benchmarks/a_vs_a_1000_t36.txt b/benchmarks/a_vs_a_1000_t36.txt deleted file mode 100644 index 00c92a3..0000000 --- a/benchmarks/a_vs_a_1000_t36.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -251.5666 0:04:11 8824.62 10318.54 8824.39 8824.65 0.00 0.09 1137.10 2860.58 diff --git a/benchmarks/a_vs_a_1000_t4.txt b/benchmarks/a_vs_a_1000_t4.txt index 2a8b3b1..7163caa 100644 --- a/benchmarks/a_vs_a_1000_t4.txt +++ b/benchmarks/a_vs_a_1000_t4.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -814.4291 0:13:34 2246.58 2380.33 2243.58 2244.08 89.14 0.11 341.55 2782.05 +772.9444 0:12:52 1819.76 6178.29 1808.91 1813.68 0.00 7.23 348.01 2693.80 diff --git a/benchmarks/a_vs_a_1000_t40.txt b/benchmarks/a_vs_a_1000_t40.txt deleted file mode 100644 index 5c648fa..0000000 --- a/benchmarks/a_vs_a_1000_t40.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -238.9409 0:03:58 8506.40 10415.53 8506.89 8507.14 0.00 0.09 1244.47 2973.60 diff --git a/benchmarks/a_vs_a_1000_t44.txt b/benchmarks/a_vs_a_1000_t44.txt deleted file mode 100644 index 2addce1..0000000 --- a/benchmarks/a_vs_a_1000_t44.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -245.7476 0:04:05 8379.21 9790.57 8344.01 8344.26 0.00 0.09 1296.98 3187.36 diff --git a/benchmarks/a_vs_a_1000_t48.txt b/benchmarks/a_vs_a_1000_t48.txt deleted file mode 100644 index 24b0a55..0000000 --- a/benchmarks/a_vs_a_1000_t48.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -241.0681 0:04:01 9230.72 11133.08 9231.52 9231.79 0.00 0.09 1355.70 3268.05 diff --git a/benchmarks/a_vs_a_1000_t52.txt b/benchmarks/a_vs_a_1000_t52.txt deleted file mode 100644 index c7e5fd6..0000000 --- a/benchmarks/a_vs_a_1000_t52.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -223.5677 0:03:43 10619.46 12665.91 10614.17 10614.42 0.00 0.09 1544.32 3452.60 diff --git a/benchmarks/a_vs_a_1000_t56.txt b/benchmarks/a_vs_a_1000_t56.txt deleted file mode 100644 index 3ce463e..0000000 --- a/benchmarks/a_vs_a_1000_t56.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -234.5145 0:03:54 11987.94 14488.64 11988.18 11988.46 0.00 0.09 1590.29 3729.21 diff --git a/benchmarks/a_vs_a_1000_t60.txt b/benchmarks/a_vs_a_1000_t60.txt deleted file mode 100644 index fa92127..0000000 --- a/benchmarks/a_vs_a_1000_t60.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -224.8990 0:03:44 10211.46 12303.54 10175.39 10175.67 0.00 0.09 1699.32 3821.86 diff --git a/benchmarks/a_vs_a_1000_t64.txt b/benchmarks/a_vs_a_1000_t64.txt deleted file mode 100644 index 5255304..0000000 --- a/benchmarks/a_vs_a_1000_t64.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -268.0256 0:04:28 11262.78 13753.96 11263.22 11263.51 8681.05 0.09 1430.49 3833.95 diff --git a/benchmarks/a_vs_a_1000_t8.txt b/benchmarks/a_vs_a_1000_t8.txt index 276228f..50ffdf1 100644 --- a/benchmarks/a_vs_a_1000_t8.txt +++ b/benchmarks/a_vs_a_1000_t8.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -484.0369 0:08:04 2661.74 3352.14 2661.75 2662.25 1189.09 0.11 649.08 3142.19 +392.3600 0:06:32 3484.98 8259.04 3389.76 3394.62 0.00 7.12 693.65 2725.33 diff --git a/environment.yml b/environment.yml new file mode 100644 index 0000000..7582f99 --- /dev/null +++ b/environment.yml @@ -0,0 +1,11 @@ +name: branchwater-bench +channels: + - conda-forge + - bioconda + - defaults +dependencies: + - sourmash>=4.8.3,<5 + - snakemake-minimal + - pip + - pip: + - pyo3_branchwater>=0.5.0 From 3be0e648836cccde82f09db20ac4e2c885b33cf3 Mon Sep 17 00:00:00 2001 From: "C. Titus Brown" Date: Sun, 20 Aug 2023 15:26:37 -0700 Subject: [PATCH 02/27] add rust, maturin, and version bounds on snakemake --- environment.yml | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/environment.yml b/environment.yml index 7582f99..e6921a6 100644 --- a/environment.yml +++ b/environment.yml @@ -5,7 +5,9 @@ channels: - defaults dependencies: - sourmash>=4.8.3,<5 - - snakemake-minimal + - snakemake-minimal>=7,<8 - pip + - rust + - maturin>=1,<2 - pip: - pyo3_branchwater>=0.5.0 From 5692c120b9556cfec5e0806f3d1a0ccd4720e155 Mon Sep 17 00:00:00 2001 From: "C. Titus Brown" Date: Sun, 20 Aug 2023 19:51:14 -0700 Subject: [PATCH 03/27] req pyo3_branchwater 0.5.1 --- environment.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/environment.yml b/environment.yml index e6921a6..fb57584 100644 --- a/environment.yml +++ b/environment.yml @@ -10,4 +10,4 @@ dependencies: - rust - maturin>=1,<2 - pip: - - pyo3_branchwater>=0.5.0 + - pyo3_branchwater>=0.5.1 From ea3c0ed7c6d8c39a099cbf898cb5cfae119d0bb5 Mon Sep 17 00:00:00 2001 From: "C. Titus Brown" Date: Mon, 21 Aug 2023 05:56:38 -0700 Subject: [PATCH 04/27] update README --- README.md | 12 ++++++++++++ 1 file changed, 12 insertions(+) diff --git a/README.md b/README.md index 8b21267..8f6309f 100644 --- a/README.md +++ b/README.md @@ -1,3 +1,15 @@ +## Running + +``` +srun -p high2 --time=72:00:00 --nodes=1 --cpus-per-task 64 --mem 64GB --pty bash +``` + +then + +``` +snakemake -j 64 -n -s benchmarking.snakefile +``` + ## command to get file sizes ``` From 83a5b6a2a115d0ba78c0e48ef02c90814a823a8d Mon Sep 17 00:00:00 2001 From: "C. Titus Brown" Date: Mon, 21 Aug 2023 08:27:23 -0700 Subject: [PATCH 05/27] add limiting resources to force no more than one rule at a time --- README.md | 10 ++++++---- benchmarking.snakefile | 20 ++++++++++++++++++++ benchmarks/a_100_vs_a.txt | 2 -- benchmarks/a_200_vs_a.txt | 2 -- benchmarks/a_300_vs_a.txt | 2 -- benchmarks/a_400_vs_a.txt | 2 -- benchmarks/a_500_vs_a.txt | 2 -- benchmarks/a_600_vs_a.txt | 2 -- benchmarks/a_700_vs_a.txt | 2 -- benchmarks/a_800_vs_a.txt | 2 -- benchmarks/a_900_vs_a.txt | 2 -- benchmarks/a_vs_a.txt | 2 -- benchmarks/a_vs_a_1000.txt | 2 -- benchmarks/a_vs_a_1000_t16.txt | 2 +- benchmarks/a_vs_a_1000_t4.txt | 2 -- benchmarks/a_vs_a_1000_t8.txt | 2 +- benchmarks/a_vs_a_2000.txt | 2 -- benchmarks/a_vs_a_3000.txt | 2 -- benchmarks/a_vs_a_4000.txt | 2 -- benchmarks/a_vs_a_5000.txt | 2 -- benchmarks/a_vs_a_6000.txt | 2 -- benchmarks/a_vs_a_7000.txt | 2 -- benchmarks/a_vs_a_8000.txt | 2 -- benchmarks/a_vs_a_9000.txt | 2 -- benchmarks/a_vs_b.txt | 2 -- benchmarks/a_vs_c.txt | 2 -- benchmarks/a_vs_catalog.txt | 2 -- benchmarks/a_vs_d.txt | 2 -- benchmarks/a_vs_e.txt | 2 -- benchmarks/a_vs_largest_10k.txt | 2 -- 30 files changed, 28 insertions(+), 58 deletions(-) delete mode 100644 benchmarks/a_100_vs_a.txt delete mode 100644 benchmarks/a_200_vs_a.txt delete mode 100644 benchmarks/a_300_vs_a.txt delete mode 100644 benchmarks/a_400_vs_a.txt delete mode 100644 benchmarks/a_500_vs_a.txt delete mode 100644 benchmarks/a_600_vs_a.txt delete mode 100644 benchmarks/a_700_vs_a.txt delete mode 100644 benchmarks/a_800_vs_a.txt delete mode 100644 benchmarks/a_900_vs_a.txt delete mode 100644 benchmarks/a_vs_a.txt delete mode 100644 benchmarks/a_vs_a_1000.txt delete mode 100644 benchmarks/a_vs_a_1000_t4.txt delete mode 100644 benchmarks/a_vs_a_2000.txt delete mode 100644 benchmarks/a_vs_a_3000.txt delete mode 100644 benchmarks/a_vs_a_4000.txt delete mode 100644 benchmarks/a_vs_a_5000.txt delete mode 100644 benchmarks/a_vs_a_6000.txt delete mode 100644 benchmarks/a_vs_a_7000.txt delete mode 100644 benchmarks/a_vs_a_8000.txt delete mode 100644 benchmarks/a_vs_a_9000.txt delete mode 100644 benchmarks/a_vs_b.txt delete mode 100644 benchmarks/a_vs_c.txt delete mode 100644 benchmarks/a_vs_catalog.txt delete mode 100644 benchmarks/a_vs_d.txt delete mode 100644 benchmarks/a_vs_e.txt delete mode 100644 benchmarks/a_vs_largest_10k.txt diff --git a/README.md b/README.md index 8f6309f..17d9e97 100644 --- a/README.md +++ b/README.md @@ -1,16 +1,18 @@ ## Running -``` -srun -p high2 --time=72:00:00 --nodes=1 --cpus-per-task 64 --mem 64GB --pty bash +```! +srun -p high2 --time=72:00:00 --nodes=1 --cpus-per-task 64 --mem 64GB --pty bash ``` then ``` -snakemake -j 64 -n -s benchmarking.snakefile +snakemake -j 64 -s benchmarking.snakefile --resources only_one_job=1 ``` -## command to get file sizes +## appendix + +### command to get file sizes ``` find . -type f -printf "%k %p\n" | tee ~/scratch/magsearch/ls-wort.txt diff --git a/benchmarking.snakefile b/benchmarking.snakefile index 6de2c2c..5bae984 100644 --- a/benchmarking.snakefile +++ b/benchmarking.snakefile @@ -22,6 +22,8 @@ rule a_vs_a: against="data/wort-list-a.txt", output: csv="outputs/output_a_vs_a.csv", + resources: + only_one_job=1, benchmark: "benchmarks/a_vs_a.txt" threads: 32 @@ -37,6 +39,8 @@ rule a_sub_vs_a: against="data/wort-list-a.txt", output: csv="outputs/output_a_{n}_vs_a.csv", + resources: + only_one_job=1, benchmark: "benchmarks/a_{n}_vs_a.txt" threads: 32 @@ -52,6 +56,8 @@ rule a_vs_a_sub: against="data/wort-list-a-{n}.txt", output: csv="outputs/output_a_vs_a_{n}.csv", + resources: + only_one_job=1, benchmark: "benchmarks/a_vs_a_{n}.txt" threads: 32 @@ -67,6 +73,8 @@ rule a_vs_b: against="data/wort-list-b.txt", output: csv="outputs/output_a_vs_b.csv", + resources: + only_one_job=1, benchmark: "benchmarks/a_vs_b.txt" threads: 32 @@ -82,6 +90,8 @@ rule a_vs_c: against="data/wort-list-c.txt", output: csv="outputs/output_a_vs_c.csv", + resources: + only_one_job=1, benchmark: "benchmarks/a_vs_c.txt" threads: 32 @@ -97,6 +107,8 @@ rule a_vs_d: against="data/wort-list-d.txt", output: csv="outputs/output_a_vs_d.csv", + resources: + only_one_job=1, benchmark: "benchmarks/a_vs_d.txt" threads: 32 @@ -112,6 +124,8 @@ rule a_vs_e: against="data/wort-list-e.txt", output: csv="outputs/output_a_vs_e.csv", + resources: + only_one_job=1, benchmark: "benchmarks/a_vs_e.txt" threads: 32 @@ -127,6 +141,8 @@ rule a_vs_largest: against="data/wort-largest-10k.txt", output: csv="outputs/output_a_vs_largest_10k.csv", + resources: + only_one_job=1, benchmark: "benchmarks/a_vs_largest_10k.txt" threads: 32 @@ -142,6 +158,8 @@ rule a_vs_a_sub_threads: against="data/wort-list-a-{n}.txt", output: csv="outputs/output_a_vs_a_{n}_t{thr}.csv", + resources: + only_one_job=1, benchmark: "benchmarks/a_vs_a_{n}_t{thr}.txt" threads: 64 # max out threads so nothing else running @@ -158,6 +176,8 @@ rule a_vs_catalog: against="data/metagenomes-catalog.txt", output: csv="outputs/output_a_vs_catalog.csv", + resources: + only_one_job=1, benchmark: "benchmarks/a_vs_catalog.txt" threads: 32 diff --git a/benchmarks/a_100_vs_a.txt b/benchmarks/a_100_vs_a.txt deleted file mode 100644 index 639514c..0000000 --- a/benchmarks/a_100_vs_a.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -1347.0233 0:22:27 12910.21 15135.63 13073.72 13073.72 0.01 0.14 2762.70 37225.36 diff --git a/benchmarks/a_200_vs_a.txt b/benchmarks/a_200_vs_a.txt deleted file mode 100644 index 935178f..0000000 --- a/benchmarks/a_200_vs_a.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -1291.4875 0:21:31 14541.96 18260.40 14601.04 14601.05 0.01 0.24 3044.57 39323.17 diff --git a/benchmarks/a_300_vs_a.txt b/benchmarks/a_300_vs_a.txt deleted file mode 100644 index 8802ac3..0000000 --- a/benchmarks/a_300_vs_a.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -1454.4474 0:24:14 16348.15 18954.26 16429.44 16429.44 0.02 0.31 2828.24 41136.09 diff --git a/benchmarks/a_400_vs_a.txt b/benchmarks/a_400_vs_a.txt deleted file mode 100644 index 167e352..0000000 --- a/benchmarks/a_400_vs_a.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -1551.7362 0:25:51 14438.77 16864.46 14666.07 14666.08 0.02 0.40 2751.87 42702.26 diff --git a/benchmarks/a_500_vs_a.txt b/benchmarks/a_500_vs_a.txt deleted file mode 100644 index bb51e13..0000000 --- a/benchmarks/a_500_vs_a.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -1603.6622 0:26:43 18893.50 21000.83 18968.33 18968.33 0.03 0.48 2802.76 44947.46 diff --git a/benchmarks/a_600_vs_a.txt b/benchmarks/a_600_vs_a.txt deleted file mode 100644 index f8ae416..0000000 --- a/benchmarks/a_600_vs_a.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -1696.6006 0:28:16 17783.73 19868.45 17888.35 17888.35 0.03 0.59 2755.67 46753.81 diff --git a/benchmarks/a_700_vs_a.txt b/benchmarks/a_700_vs_a.txt deleted file mode 100644 index 7062d0a..0000000 --- a/benchmarks/a_700_vs_a.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -1610.4366 0:26:50 16855.73 19042.42 16989.04 16989.04 0.04 0.70 3032.36 48835.22 diff --git a/benchmarks/a_800_vs_a.txt b/benchmarks/a_800_vs_a.txt deleted file mode 100644 index 85755f6..0000000 --- a/benchmarks/a_800_vs_a.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -1770.2948 0:29:30 16316.45 19000.11 16440.92 16440.92 0.04 0.85 2863.60 50694.71 diff --git a/benchmarks/a_900_vs_a.txt b/benchmarks/a_900_vs_a.txt deleted file mode 100644 index e144d88..0000000 --- a/benchmarks/a_900_vs_a.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -1806.3763 0:30:06 16779.61 19569.78 16286.82 16286.82 95967.58 0.97 2889.70 52198.87 diff --git a/benchmarks/a_vs_a.txt b/benchmarks/a_vs_a.txt deleted file mode 100644 index 1b1d483..0000000 --- a/benchmarks/a_vs_a.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -1394.1251 0:23:14 16106.77 18410.19 16167.91 16167.94 95974.41 1.14 2914.11 40626.79 diff --git a/benchmarks/a_vs_a_1000.txt b/benchmarks/a_vs_a_1000.txt deleted file mode 100644 index 0bc38be..0000000 --- a/benchmarks/a_vs_a_1000.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -154.1568 0:02:34 8026.29 8707.47 8042.18 8042.25 0.07 0.11 2112.52 3256.75 diff --git a/benchmarks/a_vs_a_1000_t16.txt b/benchmarks/a_vs_a_1000_t16.txt index 7f416a7..13e626a 100644 --- a/benchmarks/a_vs_a_1000_t16.txt +++ b/benchmarks/a_vs_a_1000_t16.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -230.3860 0:03:50 5268.45 10198.34 5316.96 5321.81 0.00 6.98 1179.52 2721.43 +241.8623 0:04:01 4217.00 13616.37 4178.51 4181.75 0.00 7.04 1126.57 2729.88 diff --git a/benchmarks/a_vs_a_1000_t4.txt b/benchmarks/a_vs_a_1000_t4.txt deleted file mode 100644 index 7163caa..0000000 --- a/benchmarks/a_vs_a_1000_t4.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -772.9444 0:12:52 1819.76 6178.29 1808.91 1813.68 0.00 7.23 348.01 2693.80 diff --git a/benchmarks/a_vs_a_1000_t8.txt b/benchmarks/a_vs_a_1000_t8.txt index 50ffdf1..6fda201 100644 --- a/benchmarks/a_vs_a_1000_t8.txt +++ b/benchmarks/a_vs_a_1000_t8.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -392.3600 0:06:32 3484.98 8259.04 3389.76 3394.62 0.00 7.12 693.65 2725.33 +366.8955 0:06:06 3893.58 13670.58 3891.74 3894.74 106.28 7.14 658.99 2422.29 diff --git a/benchmarks/a_vs_a_2000.txt b/benchmarks/a_vs_a_2000.txt deleted file mode 100644 index da9d268..0000000 --- a/benchmarks/a_vs_a_2000.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -269.0769 0:04:29 8977.02 9920.71 8961.81 8961.88 0.13 0.25 2450.90 6594.63 diff --git a/benchmarks/a_vs_a_3000.txt b/benchmarks/a_vs_a_3000.txt deleted file mode 100644 index 64a0561..0000000 --- a/benchmarks/a_vs_a_3000.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -354.2737 0:05:54 11786.54 13038.87 11863.02 11863.11 0.20 0.36 2943.38 10428.58 diff --git a/benchmarks/a_vs_a_4000.txt b/benchmarks/a_vs_a_4000.txt deleted file mode 100644 index e59e458..0000000 --- a/benchmarks/a_vs_a_4000.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -478.0915 0:07:58 13964.38 15485.38 14074.45 14074.53 0.26 0.48 3003.24 14358.91 diff --git a/benchmarks/a_vs_a_5000.txt b/benchmarks/a_vs_a_5000.txt deleted file mode 100644 index 0f47ec4..0000000 --- a/benchmarks/a_vs_a_5000.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -704.6193 0:11:44 15294.20 18001.37 15028.22 15028.30 0.33 0.64 2722.32 19182.34 diff --git a/benchmarks/a_vs_a_6000.txt b/benchmarks/a_vs_a_6000.txt deleted file mode 100644 index 5592013..0000000 --- a/benchmarks/a_vs_a_6000.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -1073.2904 0:17:53 12150.98 14048.74 12201.99 12201.99 0.39 0.73 2635.62 28288.41 diff --git a/benchmarks/a_vs_a_7000.txt b/benchmarks/a_vs_a_7000.txt deleted file mode 100644 index 9abd196..0000000 --- a/benchmarks/a_vs_a_7000.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -1269.1121 0:21:09 15887.25 17586.37 15507.43 15507.43 0.46 0.79 2923.52 37104.07 diff --git a/benchmarks/a_vs_a_8000.txt b/benchmarks/a_vs_a_8000.txt deleted file mode 100644 index b468ad0..0000000 --- a/benchmarks/a_vs_a_8000.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -1419.2742 0:23:39 16026.34 18511.11 16068.09 16068.09 0.52 0.89 3018.64 42844.40 diff --git a/benchmarks/a_vs_a_9000.txt b/benchmarks/a_vs_a_9000.txt deleted file mode 100644 index 2bfc75a..0000000 --- a/benchmarks/a_vs_a_9000.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -1576.3652 0:26:16 16715.54 19374.40 16759.83 16759.83 7.45 1.00 3052.70 48122.82 diff --git a/benchmarks/a_vs_b.txt b/benchmarks/a_vs_b.txt deleted file mode 100644 index cd2ef1f..0000000 --- a/benchmarks/a_vs_b.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -1394.1750 0:23:14 17553.49 20057.43 17685.95 17685.99 94003.57 1.16 2771.80 38643.81 diff --git a/benchmarks/a_vs_c.txt b/benchmarks/a_vs_c.txt deleted file mode 100644 index 823f9c2..0000000 --- a/benchmarks/a_vs_c.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -1357.7237 0:22:37 18257.87 20041.38 18277.77 18277.80 91280.15 1.01 2794.07 37936.37 diff --git a/benchmarks/a_vs_catalog.txt b/benchmarks/a_vs_catalog.txt deleted file mode 100644 index daba32e..0000000 --- a/benchmarks/a_vs_catalog.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -125090.2216 1 day, 10:44:50 38624.68 42192.40 38807.58 38808.14 7265572.11 87.13 2961.77 3704886.43 diff --git a/benchmarks/a_vs_d.txt b/benchmarks/a_vs_d.txt deleted file mode 100644 index 47793a7..0000000 --- a/benchmarks/a_vs_d.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -1505.0091 0:25:05 16107.48 19187.17 16137.28 16137.32 93738.74 1.02 2605.24 39209.39 diff --git a/benchmarks/a_vs_e.txt b/benchmarks/a_vs_e.txt deleted file mode 100644 index 2398eb6..0000000 --- a/benchmarks/a_vs_e.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -1596.4828 0:26:36 14046.44 15868.38 14061.43 14061.46 91948.11 0.96 2367.13 37791.57 diff --git a/benchmarks/a_vs_largest_10k.txt b/benchmarks/a_vs_largest_10k.txt deleted file mode 100644 index ce95707..0000000 --- a/benchmarks/a_vs_largest_10k.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -35660.1640 9:54:20 59988.88 70891.44 59716.36 59716.39 2225534.90 1.58 2867.89 1022695.90 From 07122a4ee2a61633b5ebeee948740662fbef4128 Mon Sep 17 00:00:00 2001 From: "C. Titus Brown" Date: Mon, 21 Aug 2023 09:48:08 -0700 Subject: [PATCH 06/27] update README again --- README.md | 12 ++++++++++-- 1 file changed, 10 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 17d9e97..a33290e 100644 --- a/README.md +++ b/README.md @@ -1,11 +1,19 @@ +# Benchmarks for branchwater paper + +This repo contains the benchmarking code for + +[Sourmash Branchwater Enables Lightweight Petabyte-Scale Sequence Search](https://dib-lab.github.io/2022-paper-branchwater-software/) ([github repo](https://github.com/dib-lab/2022-paper-branchwater-software/)), Irber et al., 2022. + +[doi: 10.1101/2022.11.02.514947](https://www.biorxiv.org/content/10.1101/2022.11.02.514947v1.full) + ## Running +Allocate 64 threads and 64 GB: ```! srun -p high2 --time=72:00:00 --nodes=1 --cpus-per-task 64 --mem 64GB --pty bash ``` -then - +then run the snakemake workflow: ``` snakemake -j 64 -s benchmarking.snakefile --resources only_one_job=1 ``` From 250284665fd929f736b5f65411673bf65ed11622 Mon Sep 17 00:00:00 2001 From: "C. Titus Brown" Date: Thu, 24 Aug 2023 13:27:52 -0700 Subject: [PATCH 07/27] updated benchmarks --- README.md | 2 +- benchmarks/a_100_vs_a.txt | 2 ++ benchmarks/a_200_vs_a.txt | 2 ++ benchmarks/a_300_vs_a.txt | 2 ++ benchmarks/a_400_vs_a.txt | 2 ++ benchmarks/a_500_vs_a.txt | 2 ++ benchmarks/a_600_vs_a.txt | 2 ++ benchmarks/a_700_vs_a.txt | 2 ++ benchmarks/a_800_vs_a.txt | 2 ++ benchmarks/a_900_vs_a.txt | 2 ++ benchmarks/a_vs_a.txt | 2 ++ benchmarks/a_vs_a_1000.txt | 2 ++ benchmarks/a_vs_a_1000_t4.txt | 2 ++ benchmarks/a_vs_a_2000.txt | 2 ++ benchmarks/a_vs_a_3000.txt | 2 ++ benchmarks/a_vs_a_4000.txt | 2 ++ benchmarks/a_vs_a_5000.txt | 2 ++ benchmarks/a_vs_a_6000.txt | 2 ++ benchmarks/a_vs_a_7000.txt | 2 ++ benchmarks/a_vs_a_8000.txt | 2 ++ benchmarks/a_vs_a_9000.txt | 2 ++ benchmarks/a_vs_b.txt | 2 ++ benchmarks/a_vs_c.txt | 2 ++ benchmarks/a_vs_catalog.txt | 2 ++ benchmarks/a_vs_d.txt | 2 ++ benchmarks/a_vs_e.txt | 2 ++ benchmarks/a_vs_largest_10k.txt | 2 ++ 27 files changed, 53 insertions(+), 1 deletion(-) create mode 100644 benchmarks/a_100_vs_a.txt create mode 100644 benchmarks/a_200_vs_a.txt create mode 100644 benchmarks/a_300_vs_a.txt create mode 100644 benchmarks/a_400_vs_a.txt create mode 100644 benchmarks/a_500_vs_a.txt create mode 100644 benchmarks/a_600_vs_a.txt create mode 100644 benchmarks/a_700_vs_a.txt create mode 100644 benchmarks/a_800_vs_a.txt create mode 100644 benchmarks/a_900_vs_a.txt create mode 100644 benchmarks/a_vs_a.txt create mode 100644 benchmarks/a_vs_a_1000.txt create mode 100644 benchmarks/a_vs_a_1000_t4.txt create mode 100644 benchmarks/a_vs_a_2000.txt create mode 100644 benchmarks/a_vs_a_3000.txt create mode 100644 benchmarks/a_vs_a_4000.txt create mode 100644 benchmarks/a_vs_a_5000.txt create mode 100644 benchmarks/a_vs_a_6000.txt create mode 100644 benchmarks/a_vs_a_7000.txt create mode 100644 benchmarks/a_vs_a_8000.txt create mode 100644 benchmarks/a_vs_a_9000.txt create mode 100644 benchmarks/a_vs_b.txt create mode 100644 benchmarks/a_vs_c.txt create mode 100644 benchmarks/a_vs_catalog.txt create mode 100644 benchmarks/a_vs_d.txt create mode 100644 benchmarks/a_vs_e.txt create mode 100644 benchmarks/a_vs_largest_10k.txt diff --git a/README.md b/README.md index a33290e..025a6a5 100644 --- a/README.md +++ b/README.md @@ -10,7 +10,7 @@ This repo contains the benchmarking code for Allocate 64 threads and 64 GB: ```! -srun -p high2 --time=72:00:00 --nodes=1 --cpus-per-task 64 --mem 64GB --pty bash +srun -p high2 --time=72:00:00 --nodes=1 --cpus-per-task 64 --mem 80GB --pty bash ``` then run the snakemake workflow: diff --git a/benchmarks/a_100_vs_a.txt b/benchmarks/a_100_vs_a.txt new file mode 100644 index 0000000..8ee8445 --- /dev/null +++ b/benchmarks/a_100_vs_a.txt @@ -0,0 +1,2 @@ +s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time +8046.1403 2:14:06 10401.48 58493.38 10403.37 10403.95 72282.79 7.61 378.65 30478.66 diff --git a/benchmarks/a_200_vs_a.txt b/benchmarks/a_200_vs_a.txt new file mode 100644 index 0000000..3d22303 --- /dev/null +++ b/benchmarks/a_200_vs_a.txt @@ -0,0 +1,2 @@ +s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time +6634.0672 1:50:34 10220.22 55552.64 10231.77 10232.34 60197.02 16.52 454.59 30161.81 diff --git a/benchmarks/a_300_vs_a.txt b/benchmarks/a_300_vs_a.txt new file mode 100644 index 0000000..f8d4027 --- /dev/null +++ b/benchmarks/a_300_vs_a.txt @@ -0,0 +1,2 @@ +s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time +6791.2807 1:53:11 10283.14 50499.57 10275.11 10275.26 57833.04 23.31 448.54 30472.00 diff --git a/benchmarks/a_400_vs_a.txt b/benchmarks/a_400_vs_a.txt new file mode 100644 index 0000000..26c066b --- /dev/null +++ b/benchmarks/a_400_vs_a.txt @@ -0,0 +1,2 @@ +s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time +5399.0796 1:29:59 10114.58 46904.75 10116.12 10116.37 47400.44 29.00 562.59 30399.56 diff --git a/benchmarks/a_500_vs_a.txt b/benchmarks/a_500_vs_a.txt new file mode 100644 index 0000000..ab7ca97 --- /dev/null +++ b/benchmarks/a_500_vs_a.txt @@ -0,0 +1,2 @@ +s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time +7236.9012 2:00:36 10306.49 58546.62 10235.79 10236.42 64539.15 35.26 446.27 32299.50 diff --git a/benchmarks/a_600_vs_a.txt b/benchmarks/a_600_vs_a.txt new file mode 100644 index 0000000..66d5737 --- /dev/null +++ b/benchmarks/a_600_vs_a.txt @@ -0,0 +1,2 @@ +s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time +8307.0373 2:18:27 10262.73 54648.19 10253.57 10254.16 69524.23 42.31 404.21 33580.93 diff --git a/benchmarks/a_700_vs_a.txt b/benchmarks/a_700_vs_a.txt new file mode 100644 index 0000000..0bb70c4 --- /dev/null +++ b/benchmarks/a_700_vs_a.txt @@ -0,0 +1,2 @@ +s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time +5935.0510 1:38:55 10436.12 51007.27 10450.90 10451.52 54838.95 50.85 562.69 33401.60 diff --git a/benchmarks/a_800_vs_a.txt b/benchmarks/a_800_vs_a.txt new file mode 100644 index 0000000..156c0da --- /dev/null +++ b/benchmarks/a_800_vs_a.txt @@ -0,0 +1,2 @@ +s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time +6634.9251 1:50:34 10577.44 45540.72 10551.79 10552.37 57337.78 58.04 527.36 34999.19 diff --git a/benchmarks/a_900_vs_a.txt b/benchmarks/a_900_vs_a.txt new file mode 100644 index 0000000..fcaaf56 --- /dev/null +++ b/benchmarks/a_900_vs_a.txt @@ -0,0 +1,2 @@ +s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time +6092.0311 1:41:32 10244.95 45939.66 10276.76 10277.33 52401.86 66.00 595.16 36253.98 diff --git a/benchmarks/a_vs_a.txt b/benchmarks/a_vs_a.txt new file mode 100644 index 0000000..6a458c4 --- /dev/null +++ b/benchmarks/a_vs_a.txt @@ -0,0 +1,2 @@ +s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time +6410.4036 1:46:50 10456.73 46762.75 10474.48 10474.75 54614.34 73.48 586.18 37592.65 diff --git a/benchmarks/a_vs_a_1000.txt b/benchmarks/a_vs_a_1000.txt new file mode 100644 index 0000000..31706a2 --- /dev/null +++ b/benchmarks/a_vs_a_1000.txt @@ -0,0 +1,2 @@ +s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time +190.5965 0:03:10 7835.11 13411.27 7682.85 7684.71 23.64 6.94 1537.50 2934.33 diff --git a/benchmarks/a_vs_a_1000_t4.txt b/benchmarks/a_vs_a_1000_t4.txt new file mode 100644 index 0000000..722b4f2 --- /dev/null +++ b/benchmarks/a_vs_a_1000_t4.txt @@ -0,0 +1,2 @@ +s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time +635.5993 0:10:35 2276.08 10742.91 2258.54 2263.37 0.00 7.33 376.03 2394.75 diff --git a/benchmarks/a_vs_a_2000.txt b/benchmarks/a_vs_a_2000.txt new file mode 100644 index 0000000..c450788 --- /dev/null +++ b/benchmarks/a_vs_a_2000.txt @@ -0,0 +1,2 @@ +s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time +492.1393 0:08:12 9266.73 19072.92 9177.62 9178.36 2893.39 14.18 1306.44 6433.30 diff --git a/benchmarks/a_vs_a_3000.txt b/benchmarks/a_vs_a_3000.txt new file mode 100644 index 0000000..ff3210c --- /dev/null +++ b/benchmarks/a_vs_a_3000.txt @@ -0,0 +1,2 @@ +s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time +337.1346 0:05:37 9214.48 14774.27 8796.72 8800.22 221.05 21.63 2495.44 8417.19 diff --git a/benchmarks/a_vs_a_4000.txt b/benchmarks/a_vs_a_4000.txt new file mode 100644 index 0000000..1a45f86 --- /dev/null +++ b/benchmarks/a_vs_a_4000.txt @@ -0,0 +1,2 @@ +s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time +1816.7844 0:30:16 10261.88 28934.04 10212.58 10213.18 17020.83 28.87 762.82 13863.96 diff --git a/benchmarks/a_vs_a_5000.txt b/benchmarks/a_vs_a_5000.txt new file mode 100644 index 0000000..0078c22 --- /dev/null +++ b/benchmarks/a_vs_a_5000.txt @@ -0,0 +1,2 @@ +s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time +4308.3585 1:11:48 10222.42 39749.15 10243.16 10243.61 40409.38 36.60 447.18 19284.64 diff --git a/benchmarks/a_vs_a_6000.txt b/benchmarks/a_vs_a_6000.txt new file mode 100644 index 0000000..5e876be --- /dev/null +++ b/benchmarks/a_vs_a_6000.txt @@ -0,0 +1,2 @@ +s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time +630.2757 0:10:30 14661.50 21440.07 11802.65 11805.98 56128.57 43.01 2918.98 18401.39 diff --git a/benchmarks/a_vs_a_7000.txt b/benchmarks/a_vs_a_7000.txt new file mode 100644 index 0000000..8547906 --- /dev/null +++ b/benchmarks/a_vs_a_7000.txt @@ -0,0 +1,2 @@ +s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time +4486.2303 1:14:46 10387.06 41859.28 10400.46 10401.07 40213.93 51.11 578.58 25962.25 diff --git a/benchmarks/a_vs_a_8000.txt b/benchmarks/a_vs_a_8000.txt new file mode 100644 index 0000000..cbcb13e --- /dev/null +++ b/benchmarks/a_vs_a_8000.txt @@ -0,0 +1,2 @@ +s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time +5241.6019 1:27:21 10062.63 46267.62 10062.45 10062.98 0.00 0.00 565.28 29627.37 diff --git a/benchmarks/a_vs_a_9000.txt b/benchmarks/a_vs_a_9000.txt new file mode 100644 index 0000000..b1b0084 --- /dev/null +++ b/benchmarks/a_vs_a_9000.txt @@ -0,0 +1,2 @@ +s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time +5638.5937 1:33:58 10485.32 43337.22 10510.07 10510.71 49704.38 66.75 577.80 32585.03 diff --git a/benchmarks/a_vs_b.txt b/benchmarks/a_vs_b.txt new file mode 100644 index 0000000..5319a37 --- /dev/null +++ b/benchmarks/a_vs_b.txt @@ -0,0 +1,2 @@ +s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time +10972.9724 3:02:52 10129.77 56932.70 10109.43 10110.02 84926.57 72.73 331.31 36359.01 diff --git a/benchmarks/a_vs_c.txt b/benchmarks/a_vs_c.txt new file mode 100644 index 0000000..2f860ed --- /dev/null +++ b/benchmarks/a_vs_c.txt @@ -0,0 +1,2 @@ +s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time +6546.8879 1:49:06 10403.43 52091.42 10226.46 10227.06 59158.95 73.10 530.59 34751.04 diff --git a/benchmarks/a_vs_catalog.txt b/benchmarks/a_vs_catalog.txt new file mode 100644 index 0000000..fbb34be --- /dev/null +++ b/benchmarks/a_vs_catalog.txt @@ -0,0 +1,2 @@ +s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time +11909.1569 3:18:29 10413.05 90798.36 10404.97 10405.67 95900.80 187.55 738.36 87945.42 diff --git a/benchmarks/a_vs_d.txt b/benchmarks/a_vs_d.txt new file mode 100644 index 0000000..5854eab --- /dev/null +++ b/benchmarks/a_vs_d.txt @@ -0,0 +1,2 @@ +s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time +8474.0678 2:21:14 10509.81 55628.16 10474.58 10475.17 74463.39 72.83 430.85 36527.69 diff --git a/benchmarks/a_vs_e.txt b/benchmarks/a_vs_e.txt new file mode 100644 index 0000000..e467e28 --- /dev/null +++ b/benchmarks/a_vs_e.txt @@ -0,0 +1,2 @@ +s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time +6643.4003 1:50:43 10399.51 47443.64 10452.64 10453.31 57368.30 76.80 530.69 35255.88 diff --git a/benchmarks/a_vs_largest_10k.txt b/benchmarks/a_vs_largest_10k.txt new file mode 100644 index 0000000..a125ffa --- /dev/null +++ b/benchmarks/a_vs_largest_10k.txt @@ -0,0 +1,2 @@ +s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time +25440.2672 7:04:00 54988.84 68716.06 47801.98 47806.76 2225582.01 181.20 3044.02 774410.78 From ca9a303190d2cd02f0256b0d3765947cab20a506 Mon Sep 17 00:00:00 2001 From: "C. Titus Brown" Date: Fri, 25 Aug 2023 06:53:34 -0700 Subject: [PATCH 08/27] run notebooks --- 01.basic-benchmarks.ipynb | 714 ++++++++++++------------ 02.basic-benchmarks-seaborn.ipynb | 878 +++++++++++++++--------------- 2 files changed, 796 insertions(+), 796 deletions(-) diff --git a/01.basic-benchmarks.ipynb b/01.basic-benchmarks.ipynb index 4720800..1d4f110 100644 --- a/01.basic-benchmarks.ipynb +++ b/01.basic-benchmarks.ipynb @@ -56,16 +56,16 @@ " \n", " \n", " 0\n", - " 1347.0233\n", - " 0:22:27\n", - " 12910.21\n", - " 15135.63\n", - " 13073.72\n", - " 13073.72\n", - " 0.01\n", - " 0.14\n", - " 2762.7\n", - " 37225.36\n", + " 8046.1403\n", + " 2:14:06\n", + " 10401.48\n", + " 58493.38\n", + " 10403.37\n", + " 10403.95\n", + " 72282.79\n", + " 7.61\n", + " 378.65\n", + " 30478.66\n", " 100\n", " 10000\n", " \n", @@ -74,11 +74,11 @@ "" ], "text/plain": [ - " s h:m:s max_rss max_vms max_uss max_pss io_in io_out \\\n", - "0 1347.0233 0:22:27 12910.21 15135.63 13073.72 13073.72 0.01 0.14 \n", + " s h:m:s max_rss max_vms max_uss max_pss io_in \\\n", + "0 8046.1403 2:14:06 10401.48 58493.38 10403.37 10403.95 72282.79 \n", "\n", - " mean_load cpu_time n_query n_against \n", - "0 2762.7 37225.36 100 10000 " + " io_out mean_load cpu_time n_query n_against \n", + "0 7.61 378.65 30478.66 100 10000 " ] }, "execution_count": 2, @@ -141,136 +141,136 @@ " \n", " \n", " 0\n", - " 1347.0233\n", - " 0:22:27\n", - " 12910.21\n", - " 15135.63\n", - " 13073.72\n", - " 13073.72\n", - " 0.01\n", - " 0.14\n", - " 2762.70\n", - " 37225.36\n", + " 8046.1403\n", + " 2:14:06\n", + " 10401.48\n", + " 58493.38\n", + " 10403.37\n", + " 10403.95\n", + " 72282.79\n", + " 7.61\n", + " 378.65\n", + " 30478.66\n", " 100\n", " 10000\n", " \n", " \n", " 0\n", - " 1291.4875\n", - " 0:21:31\n", - " 14541.96\n", - " 18260.40\n", - " 14601.04\n", - " 14601.05\n", - " 0.01\n", - " 0.24\n", - " 3044.57\n", - " 39323.17\n", + " 6634.0672\n", + " 1:50:34\n", + " 10220.22\n", + " 55552.64\n", + " 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1770.2948\n", - " 0:29:30\n", - " 16316.45\n", - " 19000.11\n", - " 16440.92\n", - " 16440.92\n", - " 0.04\n", - " 0.85\n", - " 2863.60\n", - " 50694.71\n", + " 6634.9251\n", + " 1:50:34\n", + " 10577.44\n", + " 45540.72\n", + " 10551.79\n", + " 10552.37\n", + " 57337.78\n", + " 58.04\n", + " 527.36\n", + " 34999.19\n", " 800\n", " 10000\n", " \n", " \n", " 0\n", - " 1806.3763\n", - " 0:30:06\n", - " 16779.61\n", - " 19569.78\n", - " 16286.82\n", - " 16286.82\n", - " 95967.58\n", - " 0.97\n", - " 2889.70\n", - " 52198.87\n", + " 6092.0311\n", + " 1:41:32\n", + " 10244.95\n", + " 45939.66\n", + " 10276.76\n", + " 10277.33\n", + " 52401.86\n", + " 66.00\n", + " 595.16\n", + " 36253.98\n", " 900\n", " 10000\n", " \n", @@ -280,26 +280,26 @@ ], "text/plain": [ " s h:m:s max_rss max_vms max_uss max_pss io_in \\\n", - "0 1347.0233 0:22:27 12910.21 15135.63 13073.72 13073.72 0.01 \n", - "0 1291.4875 0:21:31 14541.96 18260.40 14601.04 14601.05 0.01 \n", - "0 1454.4474 0:24:14 16348.15 18954.26 16429.44 16429.44 0.02 \n", - "0 1551.7362 0:25:51 14438.77 16864.46 14666.07 14666.08 0.02 \n", - "0 1603.6622 0:26:43 18893.50 21000.83 18968.33 18968.33 0.03 \n", - "0 1696.6006 0:28:16 17783.73 19868.45 17888.35 17888.35 0.03 \n", - "0 1610.4366 0:26:50 16855.73 19042.42 16989.04 16989.04 0.04 \n", - "0 1770.2948 0:29:30 16316.45 19000.11 16440.92 16440.92 0.04 \n", - "0 1806.3763 0:30:06 16779.61 19569.78 16286.82 16286.82 95967.58 \n", + "0 8046.1403 2:14:06 10401.48 58493.38 10403.37 10403.95 72282.79 \n", + "0 6634.0672 1:50:34 10220.22 55552.64 10231.77 10232.34 60197.02 \n", + "0 6791.2807 1:53:11 10283.14 50499.57 10275.11 10275.26 57833.04 \n", + "0 5399.0796 1:29:59 10114.58 46904.75 10116.12 10116.37 47400.44 \n", + "0 7236.9012 2:00:36 10306.49 58546.62 10235.79 10236.42 64539.15 \n", + "0 8307.0373 2:18:27 10262.73 54648.19 10253.57 10254.16 69524.23 \n", + "0 5935.0510 1:38:55 10436.12 51007.27 10450.90 10451.52 54838.95 \n", + "0 6634.9251 1:50:34 10577.44 45540.72 10551.79 10552.37 57337.78 \n", + "0 6092.0311 1:41:32 10244.95 45939.66 10276.76 10277.33 52401.86 \n", "\n", " io_out mean_load cpu_time n_query n_against \n", - "0 0.14 2762.70 37225.36 100 10000 \n", - "0 0.24 3044.57 39323.17 200 10000 \n", - "0 0.31 2828.24 41136.09 300 10000 \n", - "0 0.40 2751.87 42702.26 400 10000 \n", - "0 0.48 2802.76 44947.46 500 10000 \n", - "0 0.59 2755.67 46753.81 600 10000 \n", - "0 0.70 3032.36 48835.22 700 10000 \n", - "0 0.85 2863.60 50694.71 800 10000 \n", - "0 0.97 2889.70 52198.87 900 10000 " + "0 7.61 378.65 30478.66 100 10000 \n", + "0 16.52 454.59 30161.81 200 10000 \n", + "0 23.31 448.54 30472.00 300 10000 \n", + "0 29.00 562.59 30399.56 400 10000 \n", + "0 35.26 446.27 32299.50 500 10000 \n", + "0 42.31 404.21 33580.93 600 10000 \n", + "0 50.85 562.69 33401.60 700 10000 \n", + "0 58.04 527.36 34999.19 800 10000 \n", + "0 66.00 595.16 36253.98 900 10000 " ] }, "execution_count": 3, @@ -358,136 +358,136 @@ " \n", " \n", " 0\n", - " 154.1568\n", 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16759.83\n", - " 7.45\n", - " 1.00\n", - " 3052.70\n", - " 48122.82\n", + " 5638.5937\n", + " 1:33:58\n", + " 10485.32\n", + " 43337.22\n", + " 10510.07\n", + " 10510.71\n", + " 49704.38\n", + " 66.75\n", + " 577.80\n", + " 32585.03\n", " 1000\n", " 9000\n", " \n", @@ -496,27 +496,27 @@ "" ], "text/plain": [ - " s h:m:s max_rss max_vms max_uss max_pss io_in io_out \\\n", - "0 154.1568 0:02:34 8026.29 8707.47 8042.18 8042.25 0.07 0.11 \n", - "0 269.0769 0:04:29 8977.02 9920.71 8961.81 8961.88 0.13 0.25 \n", - "0 354.2737 0:05:54 11786.54 13038.87 11863.02 11863.11 0.20 0.36 \n", - "0 478.0915 0:07:58 13964.38 15485.38 14074.45 14074.53 0.26 0.48 \n", - "0 704.6193 0:11:44 15294.20 18001.37 15028.22 15028.30 0.33 0.64 \n", - "0 1073.2904 0:17:53 12150.98 14048.74 12201.99 12201.99 0.39 0.73 \n", - "0 1269.1121 0:21:09 15887.25 17586.37 15507.43 15507.43 0.46 0.79 \n", - "0 1419.2742 0:23:39 16026.34 18511.11 16068.09 16068.09 0.52 0.89 \n", - "0 1576.3652 0:26:16 16715.54 19374.40 16759.83 16759.83 7.45 1.00 \n", + " s h:m:s max_rss max_vms max_uss max_pss io_in \\\n", + "0 190.5965 0:03:10 7835.11 13411.27 7682.85 7684.71 23.64 \n", + "0 492.1393 0:08:12 9266.73 19072.92 9177.62 9178.36 2893.39 \n", + "0 337.1346 0:05:37 9214.48 14774.27 8796.72 8800.22 221.05 \n", + "0 1816.7844 0:30:16 10261.88 28934.04 10212.58 10213.18 17020.83 \n", + "0 4308.3585 1:11:48 10222.42 39749.15 10243.16 10243.61 40409.38 \n", + "0 630.2757 0:10:30 14661.50 21440.07 11802.65 11805.98 56128.57 \n", + "0 4486.2303 1:14:46 10387.06 41859.28 10400.46 10401.07 40213.93 \n", + "0 5241.6019 1:27:21 10062.63 46267.62 10062.45 10062.98 0.00 \n", + "0 5638.5937 1:33:58 10485.32 43337.22 10510.07 10510.71 49704.38 \n", "\n", - " mean_load cpu_time n_query n_against \n", - "0 2112.52 3256.75 1000 1000 \n", - "0 2450.90 6594.63 1000 2000 \n", - "0 2943.38 10428.58 1000 3000 \n", - "0 3003.24 14358.91 1000 4000 \n", - "0 2722.32 19182.34 1000 5000 \n", - "0 2635.62 28288.41 1000 6000 \n", - "0 2923.52 37104.07 1000 7000 \n", - "0 3018.64 42844.40 1000 8000 \n", - "0 3052.70 48122.82 1000 9000 " + " io_out mean_load cpu_time n_query n_against \n", + "0 6.94 1537.50 2934.33 1000 1000 \n", + "0 14.18 1306.44 6433.30 1000 2000 \n", + "0 21.63 2495.44 8417.19 1000 3000 \n", + "0 28.87 762.82 13863.96 1000 4000 \n", + "0 36.60 447.18 19284.64 1000 5000 \n", + "0 43.01 2918.98 18401.39 1000 6000 \n", + "0 51.11 578.58 25962.25 1000 7000 \n", + "0 0.00 565.28 29627.37 1000 8000 \n", + "0 66.75 577.80 32585.03 1000 9000 " ] }, "execution_count": 4, @@ -533,13 +533,13 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 14, "id": "850d18f6", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", "text/plain": [ "
" ] @@ -556,14 +556,14 @@ "\n", "ax = axs[0]\n", "ax.plot(query_line_df.n_query, query_line_df['s'] / 60, '-p')\n", - "ax.axis(xmin=0, ymin=0, ymax=35)\n", + "#ax.axis(xmin=0, ymin=0, ymax=35)\n", "ax.set_xlabel('num queries')\n", "ax.set_ylabel('walltime (m)')\n", "ax.set_title('varying number of queries (10k subjects)')\n", "\n", "ax = axs[1]\n", "ax.plot(against_line_df.n_against, against_line_df['s'] / 60, '-p')\n", - "ax.axis(xmin=0, ymin=0, ymax=35)\n", + "#ax.axis(xmin=0, ymin=0, ymax=35)\n", "ax.set_xlabel('num subject datasets')\n", "ax.set_ylabel('walltime (m)')\n", "ax.set_title('varying number of subjects (1000 queries)')\n", @@ -614,72 +614,72 @@ " \n", " \n", " 0\n", - " 1394.1251\n", - " 0:23:14\n", - " 16106.77\n", - " 18410.19\n", - " 16167.91\n", - " 16167.94\n", - " 95974.41\n", - " 1.14\n", - " 2914.11\n", - " 40626.79\n", + " 6410.4036\n", + " 1:46:50\n", + " 10456.73\n", + " 46762.75\n", + " 10474.48\n", + " 10474.75\n", + " 54614.34\n", + " 73.48\n", + " 586.18\n", + " 37592.65\n", " a\n", " \n", " \n", " 0\n", - " 1394.1750\n", - " 0:23:14\n", - " 17553.49\n", - " 20057.43\n", - " 17685.95\n", - " 17685.99\n", - " 94003.57\n", - " 1.16\n", - " 2771.80\n", - " 38643.81\n", + " 10972.9724\n", + " 3:02:52\n", + " 10129.77\n", + " 56932.70\n", + " 10109.43\n", + " 10110.02\n", + " 84926.57\n", + " 72.73\n", + " 331.31\n", + " 36359.01\n", " b\n", " \n", " \n", " 0\n", - " 1357.7237\n", - " 0:22:37\n", - " 18257.87\n", - " 20041.38\n", - " 18277.77\n", - " 18277.80\n", - " 91280.15\n", - " 1.01\n", - " 2794.07\n", - " 37936.37\n", + " 6546.8879\n", + " 1:49:06\n", + " 10403.43\n", + " 52091.42\n", + " 10226.46\n", + " 10227.06\n", + " 59158.95\n", + " 73.10\n", + " 530.59\n", + " 34751.04\n", " c\n", " \n", " \n", " 0\n", - " 1505.0091\n", - " 0:25:05\n", - " 16107.48\n", - " 19187.17\n", - " 16137.28\n", - " 16137.32\n", - " 93738.74\n", - " 1.02\n", - " 2605.24\n", - " 39209.39\n", + " 8474.0678\n", + " 2:21:14\n", + " 10509.81\n", + " 55628.16\n", + " 10474.58\n", + " 10475.17\n", + " 74463.39\n", + " 72.83\n", + " 430.85\n", + " 36527.69\n", " d\n", " \n", " \n", " 0\n", - " 1596.4828\n", - " 0:26:36\n", - " 14046.44\n", - " 15868.38\n", - " 14061.43\n", - " 14061.46\n", - " 91948.11\n", - " 0.96\n", - " 2367.13\n", - " 37791.57\n", + " 6643.4003\n", + " 1:50:43\n", + " 10399.51\n", + " 47443.64\n", + " 10452.64\n", + " 10453.31\n", + " 57368.30\n", + " 76.80\n", + " 530.69\n", + " 35255.88\n", " e\n", " \n", " \n", @@ -687,19 +687,19 @@ "" ], "text/plain": [ - " s h:m:s max_rss max_vms max_uss max_pss io_in \\\n", - "0 1394.1251 0:23:14 16106.77 18410.19 16167.91 16167.94 95974.41 \n", - "0 1394.1750 0:23:14 17553.49 20057.43 17685.95 17685.99 94003.57 \n", - "0 1357.7237 0:22:37 18257.87 20041.38 18277.77 18277.80 91280.15 \n", - "0 1505.0091 0:25:05 16107.48 19187.17 16137.28 16137.32 93738.74 \n", - "0 1596.4828 0:26:36 14046.44 15868.38 14061.43 14061.46 91948.11 \n", + " s h:m:s max_rss max_vms max_uss max_pss io_in \\\n", + "0 6410.4036 1:46:50 10456.73 46762.75 10474.48 10474.75 54614.34 \n", + "0 10972.9724 3:02:52 10129.77 56932.70 10109.43 10110.02 84926.57 \n", + "0 6546.8879 1:49:06 10403.43 52091.42 10226.46 10227.06 59158.95 \n", + "0 8474.0678 2:21:14 10509.81 55628.16 10474.58 10475.17 74463.39 \n", + "0 6643.4003 1:50:43 10399.51 47443.64 10452.64 10453.31 57368.30 \n", "\n", " io_out mean_load cpu_time ident \n", - "0 1.14 2914.11 40626.79 a \n", - "0 1.16 2771.80 38643.81 b \n", - "0 1.01 2794.07 37936.37 c \n", - "0 1.02 2605.24 39209.39 d \n", - "0 0.96 2367.13 37791.57 e " + "0 73.48 586.18 37592.65 a \n", + "0 72.73 331.31 36359.01 b \n", + "0 73.10 530.59 34751.04 c \n", + "0 72.83 430.85 36527.69 d \n", + "0 76.80 530.69 35255.88 e " ] }, "execution_count": 6, @@ -730,12 +730,12 @@ "name": "stdout", "output_type": "stream", "text": [ - "mean (minutes) 24.158385666666664, std 1.650659128576706\n" + "mean (minutes) 130.15910666666667, std 32.66056122524755\n" ] }, { "data": { - "image/png": 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+ "image/png": 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kA/AvaS0FHiaSJBkDSZIxkCRhDCRJGANJEsZAkoQxkCRhDCRJQBbrG2qSTAAPDHsd0n4cDfxg2IuQZvC6qhqdPrhoYyC9WCUZq6rOsNchzYaHiSRJxkCSZAyk+bB12AuQZstzBpIkXxlIkoyBJAljIA1MksuTPJZk17DXIs2WMZAG53PA+mEvQpoLYyANSFXdDEwOex3SXBgDSZIxkCQZA0kSxkCShDGQBibJVcAtwBuS7E6yadhrkg6Wv45CkuQrA0mSMZAkYQwkSRgDSRLGQJKEMZAkYQwkScD/AmgQ/BZkPEAoAAAAAElFTkSuQmCC\n", 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" ] @@ -766,12 +766,12 @@ "name": "stdout", "output_type": "stream", "text": [ - "mean 16414.41, std 1619.5661713403376\n" + "mean 10379.85, std 146.8695632185236\n" ] }, { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -801,12 +801,12 @@ "name": "stdout", "output_type": "stream", "text": [ - "mean 93388.996, std 1851.2003899578276\n" + "mean 66106.31, std 13045.372520597106\n" ] }, { "data": { - "image/png": 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" ] @@ -889,58 +889,58 @@ " \n", " \n", " 0\n", - " 814.4291\n", - " 0:13:34\n", - " 2246.58\n", - " 2380.33\n", - " 2243.58\n", - " 2244.08\n", - " 89.14\n", - " 0.11\n", - " 341.55\n", - " 2782.05\n", + " 635.5993\n", + " 0:10:35\n", + " 2276.08\n", + " 10742.91\n", + " 2258.54\n", + " 2263.37\n", + " 0.00\n", + " 7.33\n", + " 376.03\n", + " 2394.75\n", " 4\n", " \n", " \n", " 0\n", - " 484.0369\n", - " 0:08:04\n", - " 2661.74\n", - " 3352.14\n", - " 2661.75\n", - " 2662.25\n", - " 1189.09\n", - " 0.11\n", - " 649.08\n", - " 3142.19\n", + " 366.8955\n", + " 0:06:06\n", + " 3893.58\n", + " 13670.58\n", + " 3891.74\n", + " 3894.74\n", + " 106.28\n", + " 7.14\n", + " 658.99\n", + " 2422.29\n", " 8\n", " \n", " \n", " 0\n", - " 329.2121\n", - " 0:05:29\n", - " 6144.40\n", - " 7038.87\n", - " 6169.71\n", - " 6170.21\n", - " 7404.52\n", - " 0.10\n", - " 1137.80\n", - " 3746.52\n", + " 241.8623\n", + " 0:04:01\n", + " 4217.00\n", + " 13616.37\n", + " 4178.51\n", + " 4181.75\n", + " 0.00\n", + " 7.04\n", + " 1126.57\n", + " 2729.88\n", " 16\n", " \n", " \n", " 0\n", - " 154.1568\n", - " 0:02:34\n", - " 8026.29\n", - " 8707.47\n", - " 8042.18\n", - " 8042.25\n", - " 0.07\n", - " 0.11\n", - " 2112.52\n", - " 3256.75\n", + " 190.5965\n", + " 0:03:10\n", + " 7835.11\n", + " 13411.27\n", + " 7682.85\n", + " 7684.71\n", + " 23.64\n", + " 6.94\n", + " 1537.50\n", + " 2934.33\n", " 32\n", " \n", " \n", @@ -948,17 +948,17 @@ "" ], "text/plain": [ - " s h:m:s max_rss max_vms max_uss max_pss io_in io_out \\\n", - "0 814.4291 0:13:34 2246.58 2380.33 2243.58 2244.08 89.14 0.11 \n", - "0 484.0369 0:08:04 2661.74 3352.14 2661.75 2662.25 1189.09 0.11 \n", - "0 329.2121 0:05:29 6144.40 7038.87 6169.71 6170.21 7404.52 0.10 \n", - "0 154.1568 0:02:34 8026.29 8707.47 8042.18 8042.25 0.07 0.11 \n", + " s h:m:s max_rss max_vms max_uss max_pss io_in io_out \\\n", + "0 635.5993 0:10:35 2276.08 10742.91 2258.54 2263.37 0.00 7.33 \n", + "0 366.8955 0:06:06 3893.58 13670.58 3891.74 3894.74 106.28 7.14 \n", + "0 241.8623 0:04:01 4217.00 13616.37 4178.51 4181.75 0.00 7.04 \n", + "0 190.5965 0:03:10 7835.11 13411.27 7682.85 7684.71 23.64 6.94 \n", "\n", " mean_load cpu_time threads \n", - "0 341.55 2782.05 4 \n", - "0 649.08 3142.19 8 \n", - "0 1137.80 3746.52 16 \n", - "0 2112.52 3256.75 32 " + "0 376.03 2394.75 4 \n", + "0 658.99 2422.29 8 \n", + "0 1126.57 2729.88 16 \n", + "0 1537.50 2934.33 32 " ] }, "execution_count": 11, @@ -972,13 +972,13 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 12, "id": "8a522d68", "metadata": {}, "outputs": [ { "data": { - "image/png": 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nwJITVZf9uzPGGAOgqltF5FlgM5AD/IizpGOf200JDu9UV9LFTlULRCQDZxlIQ2Cux6mtu50xpkKpKiu2ZjJp6VYO5OajR7S8KFJoERN6RtewBEV5UoU5r0JgGHS54eT7G2OMMcaYasWtpTYciAf2AZ8Cg8vxeqOAUQCNGzcur8sYY2qQ5J0HmLQ0ja+XprEhPQt/XyGxXigpuw5wsKCoZL9aAb5c0a3RGV3La21GawQR+P0HmP0KR6WXjKmiNm7cSNu2bb0dxlH69+/PggULjhp/8cUXyc7OLnk9ZMgQ9u3bV4GRGWOMqeEGAhtUdZeq5gNfAL2BcHfJBxzeqa6ki527vQ5OscxSdbezznbGmLKwdV8OY2ekMOSlXxn4/Axe+Xkd9cOC+L9L2zH/kYGMv7UngX6HpxN8fYQBrWPO6Lo2g6K8tbkEvr0PdqyA+u28HY2pxsqjim5FKSgowM+vfG5HL774Itdddx0hISEATJ48uVyuY4w5fVX5/mVMKWwGeopICM4SjwHAAmAaMAKnk8eR3e1uAOa4239WVRWRScBHIvI8TpHMRGBeRb4RY0z1ln7gIJOXb2PSkjQWbNoLQIe4cB4dmsTQ9rHEhAUdtv+yx88v8xhsBkV5SxoO4gsrvvB2JKYa25CexUWvzOSFKevYl53PC1PWMezVmWxIzzqj8z7//PO0bduWtm3b8uKLL5aMFxQUcO2119K6dWtGjBhRMkPhoYceIikpifbt23P//fcDsGvXLi677DK6detGt27dmDVrFgCPP/44119/Pb179+b666+nZ8+erFy5suQaxTMisrKyuPnmm+nevTudOnVi4kTn81tOTg5XXXUVrVu35pJLLiEnJ+eo+F9++WXS0tI455xzOOeccwBo2rQp6enpbNy4kVatWnHjjTfSokULrr32WqZOnUrv3r1JTExk3jznM9/xrr9y5Uq6d+9Ox44dad++PevWrTujf9bG1FTldf8yprJQ1d9wil0uwmkx6gO8CTwI3CciyTg1Jsa5h4wDIt3x+4CH3POsBCYAq4DvgTutg4cx5kxl5ubz6YItXD/uN3r86yf+PnElmbn53H9eC2Y80J+Jd/ZmZJ/4o5IT5UW0Gi496Nq1qx5rqrfXvHcx7N0A9yxxln0YUwqrV6+mdevWAPzj65WsSss87r4LN+2loOjo/5f9fIQuTeoe85ikBmE8dlGb459z4UJuvPFG5s6di6rSo0cPPvjgA+rWrUt8fDwzZ86kd+/e3HzzzSQlJXHTTTdx1llnsWbNGkSEffv2ER4ezjXXXMMdd9xBnz592Lx5M+effz6rV6/m8ccf5+uvv2bmzJkEBwfzwgsvsG/fPv7xj3+wbds2+vfvz9q1a/nrX/9KUlIS1113Hfv27aN79+4sXryYN954gxUrVvDWW2+xbNkyOnfuzNy5c+nateth76Np06YsWLCAqKiow14fOHCA5s2bs3jxYtq0aUO3bt3o0KED48aNY9KkSbz99tt89dVXx73+Qw89RM+ePbn22mvJy8ujsLCQ4ODg4/47LCYiC1X18CCrqUp3LzaVUpd/TmFvdh6etzAfgfCQABY9Osh7gZlqy+7DxpiaLje/kJ/X7GTSkjR+XruTvIIiGtUNZliHBgzr2IBW9cPKPYbj3YttiUdFaH8FLP8UcvdB8LH/WDTmTAQH+LI/t+CY46dr5syZXHLJJdSq5fQxvvTSS/n1118ZNmwYcXFx9O7dG4DrrruOl19+mXvvvZegoCBGjhzJ0KFDGTp0KABTp05l1apVJefNzMzkwIEDAAwbNqzkj/orrriC8847j3/84x9MmDCBESNGAPDjjz8yadIknn32WcBpv7p582Z++eUX7rnnHgDat29P+/btT/k9xsfH066ds/SqTZs2DBgwABGhXbt2bNy48YTX79WrF0899RSpqalceumlJCYmnvL1janp8gqKqBPsz+6svMPGixT2ZOVx7nPTadOgDkmxYSQ1CCMpNozo0EAvRWuMMcZUXfmFRcxcl87XS9P4cdUODhwsIKp2INd0b8ywjg3oFBdeKbrQWYKiInS8xnkYc5pONNMB4MvFqfztyxVk5R2a6VkrwJcnhrfhkk5nVkn3WI68eYkIfn5+zJs3j59++onPPvuMV199lZ9//pmioiLmzp1LUNDR08KKkx8ADRs2JDIykmXLlvHJJ58wduxYwGln9Pnnn9OyZcsyfx+BgYf+0PHx8Sl57ePjQ0FBwQmv37p1a3r06MG3337LkCFDeOONNzj33HPLPEZjqqMDBwv4+LfNjJu5ge2ZuYgcXks60M+H/i2iKQIWbdrL10vTSrZFhwaSFBtGmwaHkhZNI2vhYzUrjDHGmMMUFSnzNu5h0tI0vlu+jb3Z+YQF+XFhu1iGdWxAz2aRla7mkyUoKtL+HVC7ni3zMGVuQOsYHpu48rCxM62i27dvX2688UYeeughVJUvv/yS999/H4DNmzczZ84cevXqxUcffUSfPn04cOAA2dnZDBkyhN69e9OsWTMAzjvvPF555RUeeOABAJYsWULHjh2Pec0rr7ySf//732RkZJTMiDj//PN55ZVXeOWVVxARFi9eTKdOnejXrx8fffQR5557LitWrGDZsmXHPGdoaCj79+8vWeJxqo53/fXr19OsWTPuueceNm/ezLJlyyxBYcxJ7Np/kHdmb+D9OZvIzC2gZ7MI/n5Rax76fDmZHrPAAv18+M8VHQgL8gcgIzufVdsyWbUtk5VpGaxKy2RWcnrJ0raQAF9a1Q8lqUFYyYyLlvVDCfI//VlkxhhjTFWkqqzYmsmkpVv5Ztk2tmXkEuzvy8CkGIZ1aEC/FlEE+lXe34+WoKgo66bChyNg5BSI6+btaEw1ExbkX+ZVdDt37syNN95I9+7dAbjlllvo1KkTGzdupGXLlrz22msl9Sduv/12MjIyGD58OLm5uagqzz//POAUqrzzzjtp3749BQUF9OvXr2R2xJFGjBjB6NGjefTRR0vGHn30Ue69917at29PUVER8fHxfPPNN9x+++3cdNNNtG7dmtatW9OlS5djnnPUqFEMHjyYBg0aMG3atFP+53C860+YMIH3338ff39/6tevz1//+tdTPrcxNcXG9Cze/HU9ny1MJb+wiMFt6nPr2Ql0jAsHYEi7Bic8vk6IP70SIumVEFkydrCgkHU7DjiJizTn8dXiND6Yuxlw6lgkRNcumWXRpkEdWseGElnblogYY4ypfpJ3HmDS0jS+XprGhvQs/H2Fs1tE89AFrRjYOoZagVXjT38rkllRcjPgP82h2y0w+P+8HY2pAo5VYNFULVYksxLei02FWp6awdgZKXy3Yht+Pj5c1qUhf+zbjGbRtcvlekVFSureHFZtc2ZZFCcv0jJyS/apHxZUkrQo/tk4IsSWiNQgdh82xlQXW/fl8PXSNCYtSWPVtkxEoFezSIZ1aMDgtvUJDwnwdojHZUUyvS2oDjQfBCu/gvOeAh/r8GqMMab6UVVmJqczdkYKs5J3Exrox6h+Cdzcuyn1yrlFmY+P0DgyhMaRIQxuG1syvicrj9XFMy3cnzN+30Whu0SkdqAfrWNDPZIWdUiMqW1LRIwxxlQ66QcOMnn5NiYtSWPBpr0AdIwL5+9DkxjaPrbcf9eWN0tQVKS2l8Lab2HLXGhylrejMcYYY8pMQWERk1ds540ZKaxMy6ReaCAPXdCKa3o0Lqkl4S0RtQLo3TyK3s0P1aLJzS/k9x37D0tafLYwlaw5TrFhPx+heb3ah820SGoQVqm/jTLGGFM9Zebm88OK7UxamsbslN0UFiktY0J54PyWXNS+AY0jQ7wdYpmxBEVFajEY/IJhxReWoDDGGFMt5OYX8umCLfz31w1s3pNNs+haPHNZOy7u1LBSF+EK8velfaNw2jcKLxkrKlI278lmZVpmyTKRWSnpfLF4a8k+DeoEkdSgjkdtizAa1Q2uFK3ZjDHGVB+5+YX8tHonk5ZuZdraXeQVFBEXEcyt/ZoxrGMDWtUP83aI5cISFBUpsDZc/jbUb+/tSIwxxpgzsi87j/fnbOKd2RvZnZVHx7hw/jqkNeclxVTZeg4+PkLTqFo0jarFhe0PLRFJP3CQ1dsyncSFO+Pi5zU7cFeIEBrkR+vi1qfuTIvEeqEE+NlyTmOMMaWXX1jEzHXpTFqaxo8rt5OVV0h0aCDXdG/MsI4N6BQXXu0T4pagqGgtL/B2BMYYY8xpS9uXw7iZG/h43may8wrp3zKa285OoEd8RLX90BRVO5C+idH0TYwuGcvJK2Stu0RkZVoGq7ZlMn7eFnLynSUi/r5C83qhJbMskhqE0To2jDrB3l3uYowxpnIpKlLmbdzDpKVpfLd8G3uz8wkL8mNo+wYM69iAns0i8a2iif/TYQkKb1jxBWTvhu5/9HYkxphqTESCgF+AQJz7/Weq+piIvAOcDWS4u96oqkvE+evyJWAIkO2OL3LPdQPwN3f/J1X13Yp7J6Yy+H3HfsbOSGHSkjQUuKh9LLeenUDr2Oo5xfRkggN86RgXXtIqFaCwSNm4O6tklsXKtExm/L6TzxelluzTqG5wySyLNu5SkQZ1gqptcscYY8zRVJXlWzOYtCSNb5ZtY3tmLsH+vgxMimFYhwb0axFVqZdJlidLUHjDmm8h5WfociP42jcppvratWsXQ4cOJS8vj5dffpm+ffuW+tglS5aQlpbGkCFDyiW2d955hwULFvDqq68yduxYQkJC+MMf/lAu1/Kig8C5qnpARPyBmSLynbvtAVX97Ij9LwAS3UcPYAzQQ0QigMeAroACC0VkkqrurZB3Ybxq/sY9jJ2ewk9rdhLs78t1PZtwS994GtWtPgW5yoqvj5AQXZuE6Npc1KFByfjO/bmHFeNclZbJlNU7KO70XifY/6hinM3r1cbf15aIGGNMdZK8cz+TlqTx9bJtbEjPwt9XOLtFNA8PacWgpBhCAuzPc/sn4A1tLoEVn8GGGdB8oLejMaZcFBQU8NNPP9GuXTv+97//nfLxS5YsYcGCBeWWoPB02223lfs1vEFVFTjgvvR3H3qCQ4YD77nHzRWRcBGJBfoDU1R1D4CITAEGAx+XV+zGu4qKlJ/W7GTsjBQWbtpL3RB/7h2YyA29mlK3lnWxOFX1QoOo1zKI/i3rlYxlHSxgzfb9h5IW2zL5YO4mDhYUARDg60OL+m4XkdgwkhrUoXVsKKFe7ohijDHm1KTuzebrpduYtDSN1dsyEYFezSK5tV8zBretb92hjmAJCm9oPhACw2DFl5agMJXWxo0bGTx4MF26dGHRokW0adOG9957j5CQEBYuXMh9993HgQMHiIqK4p133iE2Npb+/fvTsWNHZs6cydVXX81LL71ETk4OCxYsYM6cOfz666889thjHDx4kISEBN5++21q167N/PnzGT16NFlZWQQGBjJlyhT+/ve/k5OTw8yZM3n44Ye58sorS2JbuXIlN910E3l5eRQVFfH555+TmJjIe++9x7PPPouI0L59e95//32+/vprnnzySfLy8oiMjOTDDz8kJibmsPf6+OOPU7t2be6//3769+9Pjx49mDZtGvv27WPcuHH07duX7OxsbrzxRlasWEHLli1JS0vjtddeo2vXrhX9r+aUiIgvsBBoDrymqr+JyO3AUyLyd+An4CFVPQg0BLZ4HJ7qjh1v3FQzeQVFfLVkK2/+sp7knQdoGB7M4xclcUW3OPtWp4zVCvSjS5O6dGlSt2SsoLCIDelZhyUtpq7eyYQFh5aINIkM8UhaOI/6YbZExBhjKpNd+w8yebmTlFi4yZlw2jEunL8PTWJo+1jqhQV5OcLKyz5teIN/ELQcAmu+hoIXwM+yZqYU3r7w6LE2Fzu1TPKy4cPLj97e8RrodC1k7YYJRyxfuOnbk15y7dq1jBs3jt69e3PzzTfz+uuvM3r0aO6++24mTpxIdHQ0n3zyCY888ghvvfUWAHl5eSxYsACAyMjIkmUU6enpPPnkk0ydOpVatWrxzDPP8Pzzz/PQQw9x5ZVX8sknn9CtWzcyMzMJCQnhiSeeKDn2SGPHjmX06NFce+215OXlUVhYyMqVK3nyySeZPXs2UVFR7NmzB4A+ffowd+5cRIT//e9//Pvf/+a555474fsuKChg3rx5TJ48mX/84x9MnTqV119/nbp167Jq1SpWrFhBx44dT/rPrzJQ1UKgo4iEA1+KSFvgYWA7EAC8CTwIPFEW1xORUcAogMaNG5fFKU0FOHCwgI9/28y4mRvYnplLq/qhvHRVR4a0i7VlBhXIz9eHxJhQEmNCGd7RyQGqKjsyD5a0PS1OXny3YnvJcRG1Ao5aItIsqhZ+9u/OGGMqTGZuPt+v2M7XS9OYlZxOkULLmFAeOL8lF7VvQONIWxpZGpag8Ja2l8L25ZCZChHNvB2NMccUFxdH7969Abjuuut4+eWXGTx4MCtWrGDQoEEAFBYWEht7qB2f50wHT3PnzmXVqlUl58vLy6NXr16sXbuW2NhYunXrBkBY2MkL7vXq1YunnnqK1NRULr30UhITE/n555+5/PLLiYqKAiAiIgKA1NRUrrzySrZt20ZeXh7x8fEnPf+ll14KQJcuXdi4cSMAM2fOZPTo0QC0bduW9u2rVrtgVd0nItOAwar6rDt8UETeBu53X28F4jwOa+SObcVZ5uE5Pv0413kTJ+lB165dT7ScxFQCu/Yf5J3ZG3h/ziYycwvo2SyCpy9rx9ktou0b+UpCRKhfJ4j6dYI4t9Wh2V/7c/OdJSIerU/fmbWRvEJniUignw8t64ce1vq0Vf0wagXaRz9jjCkrufmF/LR6JxOXbGX62l3kFRYRFxHM7f0TGNahIS3rh3o7xCrHfkt5S+J50OJ8b0dhqpITzXgICDnx9lqRpZoxcaQj/0AREVSVNm3aMGfOnGNfqlatY46rKoMGDeLjjw8vW7B8+fJTjuuaa66hR48efPvttwwZMoQ33njjuPvefffd3HfffQwbNozp06fz+OOPn/T8gYGBAPj6+lJQUHDK8VUWIhIN5LvJiWBgEPCMiMSq6ja3a8fFwAr3kEnAXSIyHqdIZoa73w/Av0SkeC76eTizMEwVtTE9izd/Xc9nC1PJLyxicJv63Hp2wmEdKUzlFhrkT7emEXRrGlEyll9YxPpdWazalsHKrU7S4rsV2/l4nrNCSwSaRtY6bHlIm9gwokMDLSFljDGllF9YxMx16UxamsaPK7eTlVdIdGgg1/ZszLAODegYF2731DNgCQpvKf6PNi8bfPxsmYeplDZv3sycOXPo1asXH330EX369KFly5bs2rWrZDw/P5/ff/+dNm3anPBcPXv25M477yQ5OZnmzZuTlZXF1q1badmyJdu2bWP+/Pl069aN/fv3ExwcTGhoKPv37z/mudavX0+zZs2455572Lx5M8uWLWPQoEFccskl3HfffURGRrJnzx4iIiLIyMigYUNnqvS7755+Z8zevXszYcIEzjnnHFatWnVaiRUviAXedetQ+AATVPUbEfnZTV4IsAQorhI6GafFaDJOm9GbAFR1j4j8E5jv7vdEccFMU7UsT81g7IwUvluxDT8fHy7r0pA/9m1Gs+ja3g7NlAF/X2fWRMv6oVzSyRlTVbZl5Hq0Ps1g2dZ9fLt8W8lxUbUDaO3Z+jQ2jPioWvj62AdsY4wBp3j0vI17mLQ0je+Wb2Nvdj51gv25qEMDhnVoQI9mkXbPLCOWoPCmHSvhf4Pg0jeg9UXejsaYo7Rs2ZLXXnuNm2++maSkJG6//XYCAgL47LPPuOeee8jIyKCgoIB77733pAmK6Oho3nnnHa6++moOHjwIwJNPPkmLFi345JNPuPvuu8nJySE4OJipU6dyzjnn8PTTT9OxY8ejimROmDCB999/H39/f+rXr89f//pXIiIieOSRRzj77LPx9fWlU6dOvPPOOzz++ONcfvnl1K1bl3PPPZcNGzac1j+LO+64gxtuuIGkpCRatWpFmzZtqFOnzmmdq6Ko6jKg0zHGzz3O/grceZxtbwFvlWmApkKoKjOT0xk7I4VZybsJDfRjVL8Ebu7d1Ip01QAiQoPwYBqEBzMw6dASkYycfNZsO1TTYmVaJm/N3EB+obMyK8jfh1b1D69r0bp+GMEBvt56K1WWiLQEPvEYagb8HXjPHW8KbASuUNW97uy2l3ASxtnAjaq6yD3XDcDf3PM8qaqnn3k3xpyQqrJ8a4bbFjSNHZkHCfb3ZVBSDMM6NKBfi2gC/KzWT1kT1eq3RLhr165aXKSvUissgOdaQnw/uPxtb0djKpnVq1fTunVrr11/48aNDB06lBUrVpx85xqgsLCQ/Px8goKCSElJYeDAgaxdu5aAgOPPfjrWv0MRWaiqlbv1RxmpMvfiaqqgsIjvVmxn7IwUVqZlUi80kJv7xHNNj8aEWatKcwx5BUUk7zzg0UXEKcyZmessdfMRiI+qRZI7y6I4eREdGujlyE+NN+/D7oy2rTjL6O4E9qjq0yLyEFBXVR8UkSHA3TgJih7AS6raQ0QigAVAV5yW0QuBLqq693jXs/uwMacueed+Ji1JY9LSNDbuzsbfVzi7RT2GdWzAwNb1rKtVGTnevdj+6XqTrx8kDYOl4yEvCwKOvXbfGON92dnZnHPOOeTn56OqvP766ydMThjjLbn5hXy6YAv//XUDm/dk0yy6Fs9c1o6LOzUk0M++/TbHF+DnU1Kbgi7OmKqSujfnsNanizbt5eulaSXH1QsNPGymRVJsGE0ja+Fj052PZQCQoqqbRGQ4hwoQv4tTfPhBYDjwnjurba6IhItIrLvvlOIldiIyBRgMHF7cyRhzylL3ZvP1Uqct6OptmfgI9EqI5Pb+CQxuE0udEEvsVxRLUHhbm0tgwVvw+w9OZw9jKommTZva7AkPoaGh2LdQpjLbl53H+3M28c7sjezOyqNjXDh/HdKa85Ji7A9Fc9pEhLiIEOIiQji/Tf2S8X3ZeYclLValZTJzXToFRc7M3JAAX6euhUfSomX9UIL8a3yS7CoOJRRiVLW4GMh2oHgNTkNgi8cxqe7Y8cYPY+2ejSmdXfsPMnm5k5RYuMmZiNSpcTiPXZTEhe1jqRdqyyC9wRIU3takN9SOgZVfWoLCHEVVrQpwFVUdl8+ZyiltXw7jZm7g43mbyc4rpH/LaG47O4Ee8RF2/zDlJjwkgLMSojgrIapk7GBBIet2HDgsafHl4q28P3cT4CwRSYiu7bQ+bRBGUmwdkhqEEVGrZsxGE5EAYBjH6IKkqioiZfKLw9o9G3N8GTn5/LByO18vTWNWcjpFCq3qh/LA+S0Z1qEBcREh3g6xxrMEhbf5+MLQF6BOnLcjMZVMUFAQu3fvJjIy0v7IqGJUld27dxMUZJl3U35+37GfsTNSmLQkDQUuah/LrWcn0Do2zNuhmRoq0M+Xtg3r0LbhoQLCRUXOEpGVaRklSYvfNuzhqyWHlojUDwtyO4gcmnERVzekOs78uQBYpKo73Nc7PNo+xwI73fGtgOcHw0bu2FYOLQkpHp9erhEbUw3k5BXy05odTFqSxvS1u8grLKJxRAi3909gWIeGtKwf6u0QjQdLUFQGrS70dgSmEmrUqBGpqans2rXL26GY0xAUFESjRo28HYaphuZv3MPY6Sn8tGYnwf6+XNezCbf0jadRXfvWx1Q+Pj5C48gQGkeGcEG72JLxPVl5rHbbnhbPuJjx+y4K3SUitQP9aB0bWpKwaNOgDokxtQ+ro1JYpIybuZ7Xp6dwR/8ERvZpVtnb/F3N4fUiJgE3AE+7Pyd6jN8lIuNximRmuEmMH4B/iUhdd7/zOMZsDGMM5BcW8eu6XUxaksaUVTvIyiskOjSQa3s2ZliHBnSMC7cvACspS1BUFptmw/bl0ONWb0diKgl/f3/i4+O9HYYxphIoKlJ+WrOTsTNSWLhpL3VD/Ll3YCI39GpK3RoyPd5ULxG1AujdPIrezQ8tEcnNL+T3HftL2p6u2pbJpwtTyZ5TCICfj9C8Xm2SYsOoXyeIb5dtY+f+XHLyi3hhyjomLknj1Ws6Ex9V+YqOi0gtYBDg+UHvaWCCiIwENgFXuOOTcTp4JOO0Gb0JQFX3iMg/gfnufk8UF8w0xji/K3/bsIdJS9P4bsU29mXnUyfYn4s6NGBYhwb0aBZZ2ZOYBktQlKtTyuyv/gbmvQntr4Tg8AqN0xhjTOWUV1DEV0u28uYv60neeYCG4cE8flESV3SLszZnptoJ8velfaNw2jcKLxkrKlI27ck+rO3pzOR0du4/eNixOfmFrN6WyYgxs1n46KAKjvzkVDULiDxibDdOV48j91WcFqTHOs9bwFvlEaMxVZGqsiw1g0lL0/hmWRo7Mg8S7O/LoKQYhnVoQL8W0QT4+Xg7THMK7NNNOdmQnsWdHy4iZdcBDhaUIrPf9lKY+xqs+RY6XVvxARtjjKk0Dhws4OPfNjNu5ga2Z+bSqn4oL13VkSHtYvH3tQ9apubw8RHio2oRH1WLC9sfWiJy2euzWbh572H7Fim0iLG15MbUBOt27GfS0jS+XprGxt3Z+PsKZ7eoxyMXNmBg63qWxK/CvPJvTkT+BNwCKLAcZ+paLDAeJ7u8ELheVfNEJBB4D6cj927gSlXd6I24T8WIMbPZm52Hu5Ty5Jn9hl0gvDGs/MISFMYYU0Pt2n+Qd2Zv4P05m8jMLaBnswievqwdZ7eItrWyxni4rldj1mzPJCuvsGSsVoAvV3Sz2j/GVFdb9mTz9bI0Ji1JY832/fgI9EqI5Pb+CQxuE0udEH9vh2jKQIUnKESkIXAPkKSqOSIyAacn9BDgBVUdLyJjgZHAGPfnXlVtLiJXAc8AV1Z03KcqMaY2c9cfvizwhJl9EWhzCcx5DbL3QEhEBURpjDGmMtiYnsWbv67ns4Wp5BcWcX5SfW7rn0DHuHBvh2ZMpTSgdQyPTVx52JivjzCgdYyXIjLGlIdd+w/y7bI0Ji1NY9HmfQB0ahzOYxclcWH7WOqFWse06sZbc1/8gGARyQdCgG3AucA17vZ3gcdxEhTD3ecAnwGvioi46/MqrSu7xbE8NePUMvttLoGl4yF9HTTuUQFRGmOMqUhH1ibq3jSS//66nu9WbMPPx4fLujTklr7NSIiu7e1QjanUwoL8Wfb4+d4OwxhTDjJy8vlhxXYmLU1jdko6RQqt6ofywPktGdahAXER1rWqOqvwBIWqbhWRZ4HNQA7wI86Sjn2qWuDulgo0dJ83BLa4xxaISAbOMpD0Cg38FB0rs+8jJ8nsx3aE+1aDj+/x9zHGGFMlFdcm2pCeRU5+IU9/t4YihVr+vozql8DNvZtSL8y+CTLGGFPz5OQVMnX1DiYtTWPG2l3kFRbROCKEO/o3Z1jHBlZfpgbxxhKPujizIuKBfcCnwOAyOO8oYBRA48aNz/R0Z8wzs//7jv2c/+Iv/OGsJoQFnWBtlAiILxQVQVEB+FnrOGOMqS5GjJnNnuw8iuf/FSkIEODvw0MXtPJqbMYYY0xFyysoYmbyLiYtSePHVTvIziukXmgg1/VswrCODejQqI7VX6qBvLHEYyCwQVV3AYjIF0BvIFxE/NxZFI2Are7+W4E4IFVE/IA6OMUyD6OqbwJvAnTt2rVSLf9oERPKkHaxvDNrI7f0aXbinvVZ6fBGP+jzJ+j+x4oL0hhjTLlZvS2TgqIijlycqECr+mFeickYY4ypaIVFyrwNe5i0NI3vVmxjX3Y+dYL9Gd6xARd1aECP+Eh8fSwpUZN5I0GxGegpIiE4SzwGAAuAacAInE4eNwAT3f0nua/nuNt/ruz1J47lnnMT+XbZNsbN3MD957c8/o4hkRBQG1Z+aQkKY4yp4rZn5PL8lLV8ujCVID9fAnyFvMJDv8Ks64AxxpjqTlVZlprBpKVpfLMsjR2ZBwkJ8GVQUgzDOjSgb2I0AX7WQts4vFGD4jcR+QxYBBQAi3FmPnwLjBeRJ92xce4h44D3RSQZ2IPT8aPKaVk/lAvbxfLO7I3c0jee8JDjzKIQgbaXwvSnIXMbhMUeez9jjDGV1oGDBbw5I4U3f11PURGM7B3PDWc14cKXZ5JXWFCyn3UdMMYYU12t27GfSUudDhybdmcT4OvD2S2jGdahAQNa1yMkwFv9Gkxl5pX/KlT1MeCxI4bXA92PsW8ucHlFxFXe7h7QnG+XO7Mo/nzeCWZRtLkUpv8frPoKet5eYfEZY4w5MwWFRXyyYAsvTFlH+oGDDG0fy1/Ob0XjSKfiuHUdMMYYU51t2ZPN18vSmLQkjTXb9+MjcFZCFHf2b875bepTJ+QE9fiMwXttRmukVvXDuKBt/ZJaFMf9HzS6BcS0hRVfWILCGGOqAFVl2tqd/GvyGpJ3HqBb07r89w9d6NS4rrdDM8YYY8rVrv0H+XaZM1Ni0eZ9AHRuHM7jFyUxpH0s9UKtQ5UpPUtQVLB7BiTy3YrtjJu1gfsGtTj+juf+DXzsX48x5syISBDwCxCIc8//TFUfE5F4nJo/kTitnq9X1TwRCQTeA7rgFCS+UlU3uud6GBgJFAL3qOoPFf1+KqMVWzN46tvVzFm/m/ioWoy9rgvnt4mxyuPGGGOqrYycfH5YsZ1JS9OYnZJOkUKr+qH8ZXBLLmrfgLiIEG+HaKoo+wu4grWODWNwm/q8PXMDI3vHH38WRcsLKjYwY0x1dRA4V1UPiIg/MFNEvgPuA15Q1fEiMhYn8TDG/blXVZuLyFXAM8CVIpKEUwOoDdAAmCoiLVS10BtvqjLYui+H535YyxeLt1I3xJ9/DGvDNT0a4+9rhb6MMcZUPzl5hUxdvYNJS9OYsXYXeYVFNI4I4c5zmjOsQwMSY0K9HaKpBixB4QX3DEjk+5XbeWvWBv50olkU6esgZRr0GFVxwRljqhW369EB96W/+1DgXOAad/xd4HGcBMVw9znAZ8Cr4kwFGA6MV9WDwAa3cHF3nA5LNUpmbj5jpqcwbuYGAG7vn8Dt/RMIC7J1tcYYY6quwiJl3Mz1vD49hTv6JzCyTzMKi5Rf1+1i0tI0pqzaQXZeIfVCA7muZxOGdWxAh0Z1bMagKVOWoPCCpAZhnN8mhrdmbeDmPvHUCT7Oh9q1k2HK3yFxEETEV2yQxphqQ0R8cZZxNAdeA1KAfapa3E4iFWjoPm8IbAFQ1QIRycBZBtIQmOtxWs9jPK81ChgF0Lhx4zJ/L96UX1jER79t5qWf1rEnK49LOjXkz+e1oFFdm8ZqjDGmatuQnsWdHy5iQ3oWOfmFPPfj74yZnkJBkbI/t4DwEH+Gd2zIRR1i6REfia+PJSVM+bAEhZfcMyCRH1bu4O1ZG7h34HFmUSRd7CQoVn4Jfe+r0PiMMdWHuwyjo4iEA18CrcrxWm/itI6ma9euWl7XqUiqyo+rdvD0d2vYkJ5Fr2aR/HVIa9o1quPt0IwxxpgyMWLMbPZm51Hk/uY+WFDEwYIiAvx8eOvGrvRpHk2Any1hNOXP/ivzkjYN6jAoKYa3Zm4gIyf/2DvVbQINu8LKLyo2OGNMtaSq+4BpQC8gXESKk9SNgK3u861AHIC7vQ5OscyS8WMcU20t3ryXK96Yw63vL8TXR3jrxq589McelpwwxhhTrSTG1C5JTnjq0rgu57aKseSEqTD2X5oXjR6QSGZuAe/M2nj8ndpeCtuXQ3pyhcVljKk+RCTanTmBiAQDg4DVOImKEe5uNwAT3eeT3Ne4239261hMAq4SkUC3A0giMK9C3oQXbNmTzV0fLeKS12ezIT2Lpy5py/ej+3JuK+vOYYw5dSISLiKficgaEVktIr1EJEJEpojIOvdnXXdfEZGXRSRZRJaJSGeP89zg7r9ORG44/hWNOTU94iOPGqsV4MsV3Rp5IRpTk1mCwovaNqzDwNYxjJu5nszc48yiSLoY/GvBjhUVGpsxptqIBaaJyDJgPjBFVb8BHgTuc4tdRgLj3P3HAZHu+H3AQwCquhKYAKwCvgfurI4dPDKy83nq21UMeG4GU1fv4J5zmzP9gXO4tkcT/Kw7hzHm9L0EfK+qrYAOOInih4CfVDUR+Ml9DXABThI4EaemzxgAEYkAHgN64BQpfqw4qWHMmdh94CDj52/myPy7r48woHWMd4IyNZbVoPCyewcmMvSVHbw7ayN3D0g8eoc6DeEv68E/qOKDM8ZUeaq6DOh0jPH1OB9wjxzPBS4/zrmeAp4q6xgrg4MFhbw/ZxOv/JxMZm4+l3dpxH2DWlK/jt17jTFnRkTqAP2AGwFUNQ/IE5HhQH93t3eB6TjJ4+HAe+7stbnu7ItYd98pqrrHPe8UYDDwcUW9F1P9FBYp94xfzL7sfL6+qw9tG9oSRuNdlqDwMmcWRT3+N3MDN/ZuSuix2tQVJyeKCsHHt2IDNMaYakxVmbx8O898v4bNe7LpmxjFwxe0JqlBmLdDM8ZUH/HALuBtEemA01VpNBCjqtvcfbYDxV9Vl3RTchV3TTre+GGqczclU/ae+3Ets5J38+8R7S05YSoFm69aCYwe0IKMnHzenb3x2DsU5MGb58D0pys0LmOMqc4WbNzDpWNmc+dHiwgJ8OXdm7vz/sgelpwwxpQ1P6AzMEZVOwFZHFrOAYA7W6JMOh+p6puq2lVVu0ZHR5fFKU019ePK7bw+PYWrusVxRde4kx9gTAWwBEUl0K5RHQa0cmZR7D9WLQq/AAio5XTz0GrRtc8YY7xmQ3oWt72/kBFj57B1bw7/vqw9397Tl7Nb2Ad5Y0y5SAVSVfU39/VnOAmLHe7SDdyfO93tx+uaVCO7KZnysTE9iz9PWEq7hnV4fFgbb4djTAlLUFQSowcmsi87n/fmbDr2Dm0vhd3JTkcPY4wxpVJYpLz5Swodn/iRF6f+zt8nrmDQ8zP4Zd0u7hvUgukP9OeKbnH4+lhnDmNM+VDV7cAWEWnpDg3AKTjs2TXpyG5Kf3C7efQEMtylID8A54lIXbc45nnumDGnJCevkNs+WIivr/D6tZ0J8rcl5KbysBoUlUT7RuGc0zKa//66nhvOakrtwCP+1bQeDt/e78yiiG3vnSCNMaYK2ZCexZ0fLmJDehY5+YW8OHUdAEM7xPL3oUnUC7UCmMaYCnM38KGIBADrgZtwviicICIjgU3AFe6+k4EhQDKQ7e6Lqu4RkX/idGQCeKK4YKYxpaWqPPLlctbu2M/bN3YjLiLE2yEZcxibQVGJjB7Ywp1FsfHojbUiodnZsMKWeRhjTGmMGDObNdszyck/1A3VR2BO8m5LThhjKpSqLnHrQrRX1YtVda+q7lbVAaqaqKoDi5MN6rhTVRNUtZ2qLvA4z1uq2tx9vO29d2Sqqg9/28wXi7cyekAi/VvW83Y4xhzFEhSVSMe4cPq3jOa/v6wn62DB0Tv0ugv6PeB08zDG1EgiUktEbC5mKSTG1KboiHxukUKLmFDvBGSMMcZ40ZIt+3ji61X0bxnNPecmejscY47JEhSVzOgBiew9Xi2K5gOg8/XgaytzjKkpRMRHRK4RkW9FZCewBtgmIqtE5D8i0tzbMVZWV3aLo1bA4bmcWgG+XNGtkZciMsYYY7xjT1Yed3ywkHphgbx4ZUd8rPaSqaQsQVHJdGpcl7NbRPPmLynHnkVxYCcsfMeWeRhTc0wDEoCHgfqqGqeq9YA+wFzgGRG5zpsBVlYDWsccVfzS10cY0DrGSxEZY4wxFa+wSLnn48WkZ+Ux9rouhIcEeDskY47LvoqvhEYPTOTS12fz/txN3HZ2wuEbU36Gr0dDvSSI6+6dAI0xFWmgqh7Vf9hdq/w58LmI+Fd8WJVfWJA/yx4/39thGGOMMV71wpTfmZmczjOXtaNtwzreDseYE7IZFJVQ58Z16dcimjd/WU923hGzKFoOAd9Ap1imMabaK05OiEiCiAS6z/uLyD0iEu65jzHGGGOMp6mrdvDqtGSu7BrHld0aezscY07KEhSV1OgBiezJyuP9I2tRBIVB4iBY9RUUFXklNmOMV3wOFLo1J94E4oCPvBuSMcYYYyqrTbuz+NOEJbRtGMY/hrfxdjjGlIolKCqpLk3q0jcx6tizKNpcAvu3weY53gnOGOMNRapaAFwCvKKqDwCxXo7JGGOMMZVQTl4ht32wCB8RxlzbhSB/awBmqgZLUFRiowcksjsrjw/nbj58Q4vB4F8L0hZ5JzBjjDfki8jVwA3AN+6Y1Z4wxhhjzGFUlb99tYI12zN58cqOxEWEeDskY0rNEhSVWNemEfRpHsUbv6SQk1d4aENgbbhvFZx1t/eCM8ZUtJuAXsBTqrpBROKB970ckzHGGGMqmY/mbebzRancfW4i57Sq5+1wjDkllqCo5EYPTCT9QB4f/nZELYrgcOentRs1pkZQ1VWqeo+qfuy+3qCqz3g7LmOMMcZUHku37OMfk1bRr0U0owckejscY06ZJSgquW5NI+jdPJKxM9YfPosC4NObYPID3gnMGFMhRORrEbnoWK1ERaSZiDwhIjd7IzZjjKlJRKSRiNwvIhNFZL6I/CIir4vIhSJin6mN1+3JyuOODxcRHRrIS1d2xNdHvB2SMafMbqZVwOgBLUg/cPDoWRTiAys+g0LrMGhMNfZHoC+wxv1APFlEfhaR9cAbwEJVfcu7IRpjTPUmIm8DbwF5wDPA1cAdwFRgMDBTRPp5L0JT0xUWKaPHL2bX/oOMua4zdWsFeDskY06LJSiqgO7xEZyVEMkbv6wnN99jFkXbSyFnL6yf4b3gjDHlSlW3q+pfVDUBuBz4J3Af0FZVB6nqxOMdKyJxIjJNRFaJyEoRGe2OPy4iW0VkifsY4nHMwyKSLCJrReR8j/HB7liyiDxUfu/YGGMqpedU9TxVfVlVZ6tqsqquUNUvVPVuoD+Q5uUYTQ320tTf+XVdOv8Y3ob2jcK9HY4xp80SFFXE6AGJ7Np/kA9/8+jo0XwgBIbByi+8F5gxpsKo6kZVnaOqS1Q1uxSHFAB/VtUkoCdwp4gkudteUNWO7mMygLvtKqANzjeCr4uIr4j4Aq8BFwBJwNUe5zHGmGpPVVecZHueqiZXVDzGePp5zQ5e/jmZy7s04qpucd4Ox5gzYgmKKqJHs0h6Notg7IyUQ7Mo/AKh1YWw+hsoOOjdAI0xlY6qblPVRe7z/cBqoOEJDhkOjFfVg6q6AUgGuruPZFVdr6p5wHh3X2OMqRFEJFFE3hGR591aFN+JSJaILBWRbt6Oz9Rcm3dnc+/4JbRpEMY/L26LiNWdMFXbSRMUVhCo8hg9oAW79h/k43kesyg63wC974HCPO8FZoyp9ESkKdAJ+M0duktElonIWyJS1x1rCGzxOCzVHTve+LGuM0pEFojIgl27dpXlWzDGGG96G5iNs4zjN5x6FJHA/cCrXozL1GC5+YXc9sFCAMZc24Ugf18vR2TMmTthgsEKAlUuvRIi6REfwZjpHrMomvSCfvdDYKh3gzPGlDsRCRaRlqdxXG3gc+BeVc0ExgAJQEdgG/BcWcWoqm+qaldV7RodHV1WpzXGGG+r7d7fngVyVPVTVc1V1SlAoLeDMzWPqvLoVytYtS2TF67sSOPIEG+HZEyZONkMCCsIVMmMHpjIzv0HGe85iyIvG1Z+Cfk53gvMGFOuROQiYAnwvfu6o4hMKsVx/jjJiQ9V9QsAVd2hqoWqWgT8F2cJB8BWwHPxaiN37HjjxhhTUxR5PM88wbZjEpGNIrLcLUy8wB2LEJEpIrLO/VnXHRcRedktSrxMRDp7nOcGd/91InJDWbwxUzWNn7+FTxemcve5zRnQOsbb4RhTZk6YoDhWQSARqSsi7d3tVhCogvVqFkn3+AjGeNai2DIXPr0Rkqd6NTZjTLl6HCeRsA9AVZcA8Sc6QJyFqOOA1ar6vMd4rMdulwDF9/pJwFUiEigi8UAiMA+YDySKSLyIBOAU0jxpcsQYY6qRVm6yYLnH8+LXpZ3Zdo5bmLir+/oh4CdVTQR+cl+DU5A40X2Mwpn1hohEAI8BPXB+HzzmsUTP1CDLUvfx2MSV9E2M4t6BLbwdjjFlqlQ1JERkuoiEuTfGRcB/ReSF072oiISLyGciskZEVotIr9PJItdEIsK9AxLZkXmQT+a7S8Kb9oOQKFhh3TyMqcbyVTXjiDE9yTG9geuBc49oKfpv95u8ZcA5wJ8AVHUlMAFYhTNT4053pkUBcBfwA06hzQnuvsYYU1O0Bi4Chno8L359ul2NhgPvus/fBS72GH9PHXOBcDexfD4wRVX3qOpeYArOkmtTg+zNyuP2DxYRHRrIS1d1wtfHimKa6sWvlPvVUdVMEbkF54b5mPvB9nS9BHyvqiPcb+NCgL/iZJGfFpGHcLLID3J4FrkHTha5xxlcu8rrlRBJt6Z1GTM9hau6xxHo5wdJw2DpeMjLgoBa3g7RGFP2VorINYCviCQC9+AUbDsuVZ0JHOuTy+QTHPMU8NQxxief6DhjjKnOVHXTmZ4C+FFEFHhDVd8EYlR1m7t9O1A8T/+MChaLyCicmRc0btz4DMM2lUlhkXLvJ0vYtf8gn97Wi4haAd4OyZgyV9ouHH5u5vYK4JszuaCI1AH64Uw7Ll4mso9TzyLXWCLCvQNbsD0zlwnFsyjaXAr52fD7D94NzhhTXu4G2gAHgY9x1kDf682AjDGmphCRkSLygMfrrSKSKSL7ReS2Upyij6p2xvni7c4ji8yrqnLyWXGlYsWKq6+Xf1rHjN938diwJDrEhXs7HGPKRWkTFE/gTO1NVtX5ItIMWHea14wHdgFvi8hiEfmfiNTi1LPIh6lpre3OSoika5O6vD49hYMFhdDkLKgdAxtnejs0Y0w5UNVsVX1EVbu5HzwfUdVcb8dljDE1xG04ne2K7VTVMCAap8vdCanqVvfnTuBLnBoSO4q/dHN/7nR3t4LF5ijT1u7k5Z/XcVnnRlzT3WbGmOqrVAkKt5VSe1W9w329XlUvO81r+gGdgTGq2gnI4lBRoOLrnXIWuaZli4tnUWzLyGXCglTw8YVRM+DCMusWaIypRESkq4h8ISKLPIqznclSO2OMMaUnqrrb4/WnAG6iOPiEB4rUEpHQ4ufAeTjFiScBxZ04bgAmus8nAX9w67D1BDLcL/F+AM5zC9bXdc9jU2drgC17srl3/BJa1Q/jyYvb4tTANqZ6OmENChH5G/C6qu45zvZzgRBVPZVlH6lAqqr+5r7+DCdBsUNEYlV1WymzyDVe7+aRdGlSl9enJXNF10YEhtXolS/GVHcfAg8AyylFSztjjDFlKtzzhar+C0BEfICokxwbA3zp/lHpB3ykqt+LyHxggoiMBDbhLKUGp97PECAZyAZucq+5R0T+idNZCeCJ431GN9VHbn4ht3+4kCJVxl7XmeAAX2+HZEy5OlmRzOXA1yKSi9O9YxcQhFOwsiMwFfjXqVxQVbeLyBYRaamqa4EBOBXjV+Fkj5/m6CzyXSIyHqc4ZnEWucYTEUYPSOQPb83j0wWpXNezCfz0BGSmwSVjvR2eMaZs7VJVa+1pjDHe8aOIPKmqfzti/AngxxMdqKrrgQ7HGN+N8zn4yHEF7jzOud7i8KUmppp7bOJKVmzN5H9/6EqTSCuEb6q/EyYoVHUiMNGtGN8biMUpzPYBMEpVc07zuncDH7odPNbjZIZ9OIUssnH0TYyic+NwdxZFHAH5ubD8Mxj8NASHezs8Y0zZeUxE/gf8hFMoEwBVtf7CxhhT/h4A/iciycBSd6wDsAC4xWtRmWrtk/mb+WTBFu48J4GBSTEnP8CYaqBUbUZVdR2nXxTzWOdbAnQ9xqZTyiIbdxbFwBbc8NY8Pl24hWvbXgpzX4M130Kna70dnjGm7NwEtAL8ObTEQwFLUBhjTDlT1SzgardQfBt3eJWqpngxLFONrdiawaMTV9KneRT3DWrp7XCMqTClSlCYyq1fYhQd48J5fVoKl//5bALCG8PKLyxBYUz10k1V7ROKMcZ4gYg0VdWN7nKN9cfYLkBDVU2t+OhMdbMvO4/bPlhIVK0AXrqqI74+VhTT1BylbTNqKjGno0ciW/fl8PnirdDmElg/HbKtbpIx1chsEUnydhDGGFND/UdEPheRP4hIGxGpJyKNReRct3DlLKC1t4M0VV9RkfKnT5awIzOX167tTGTtQG+HZEyFshkU1cTZLaLpEBfOqz8nM+L6Efjn50LBwZMfaIypKnoCS0RkA04NCsFZBdfeu2EZY0z1p6qXu0nia4GbceqyZQOrceqlPeW2HDXmjLzyczLT1u7inxe3pVPjut4Ox5gKV6oEhYi0AMYAMaraVkTaA8NU9clyjc6Umohw74BEbnpnPp9vDeeqIf/2dkjGmLI12NsBGGNMTaaqq4BHvB2Hqb6mr93Jiz/9zqWdGnJdj8beDscYryjtEo//Ag8D+QCqugy4qryCMqenf8toOjSqw6vTkskvKIBNc2yZhzFVnIiEuU/3H+dhjDHGmCpuy55s7v1kCS1jQnnqknY4ZU2MqXlKm6AIUdV5R4wVlHUw5sw4HT0SSd2bw0+/zIC3BzvFMo0xVdlH7s+FOO3sFno8FngrKGOMMcaUjdz8Qu74cBGFRcrY67oQHODr7ZCM8ZrSJijSRSQBp6UdIjIC2FZuUZnTdk7LerRvVIen5oNGtYQVX3o7JGPMGVDVoe7PeFVt5v4sfjTzdnzGGGOMOTP/+Holy7dm8PwVHWkaVcvb4RjjVaVNUNwJvAG0EpGtwL3A7eUVlDl9IsLoAYls2ZvLyroDYNMsyLRckjFVnYj8VJoxY4wxZU9EmohIHY/X54jISyJyn4gEeDM2U7VNWLCFj+dt4Y7+CQxKivF2OMZ4XakSFKq6XlUHAtFAK1Xto6obyzUyc9rObVWPdg3r8PSWJEBh1URvh2SMOU0iEiQiEUCUiNQVkQj30RRo6OXwjDGmppgA1AIQkY7Ap8BmoAPwuvfCMlXZiq0ZPPrVCs5KiOS+QS28HY4xlUJpu3iEA38AmgJ+xUVbVPWe8grMnL7iWRS3vJfBvugWhK/7EXre5u2wjDGn51acWWsNcOpOFFfNygRe9VJMxhhT0wSrapr7/DrgLVV9TkR8gCXeC8tUVRnZ+dz+4ULqhgTw8tWd8PMt7cR2Y6q3UiUocPo7zwWWA0XlF44pKwNa16NtwzBuzf4zH155can/RRtjKhdVfQl4SUTuVtVXvB2PMcbUUJ4tFc7F6W6HqhZZtwVzqoqKlD9NWML2jFw+ubUXUbUDvR2SMZVGaVN1Qap6n6q+rarvFj/KNTJzRkSEe85N5Le9oXy1PN3b4RhjztDpJCdEJE5EponIKhFZKSKj3fEIEZkiIuvcn3XdcRGRl0UkWUSWiUhnj3Pd4O6/TkRuKLt3ZowxVcLPIjJBRF4C6gI/A4hILJDn1chMlfPatGR+XrOTR4cm0blxXW+HY0ylUtoExfsi8kcRifVY/xxRrpGZMzYoKYak2DA2/vAqRRNu9HY4xpiKVwD8WVWTgJ7AnSKSBDwE/KSqicBP7muAC4BE9zEKGANOQgN4DOgBdAceK05qGGNMDXEv8AWwEeijqvnueH3gES/FZKqgX37fxfNTf+fijg24vmcTb4djTKVT2gRFHvAfYA7OGuiFwILyCsqUDRFh9MBE8rL24bPqS9izwdshGWMqkKpuU9VF7vP9wGqcwprDgeJZcO8CF7vPhwPvqWMuEO5+O3g+MEVV96jqXmAKMLji3okxxniXe18cr6ovqOpWEYkUkUsAH1X9wdvxmaohdW82o8cvpkW9UP51aTtseZAxRyttguLPQHNVbaqq8e6jWXkGZsrGeUkx/B45EIDCFV94ORpjzKkSkc5HPDqJSNxpnKcp0An4DYhR1eL+w9uB4r5mDYEtHoelumPHGz/WdUaJyAIRWbBr165TDdMYYyolEflGRNq6z2OBFcDNOLOM7/VmbKZqOFhQyJ0fLqKgUBl7fRdCAqxCnDHHUtoERTKQXZ6BmPIhIlx1Xh8WFzVn/8IJ3g7HGHPqnjvi8TzwjYisdlvdnZSI1AY+B+5V1UzPbaqqgJZVsKr6pqp2VdWu0dHRZXVaY4zxtnhVXeE+vwlnVtlFOEvfbi7NCUTEV0QWi8g37ut4EfnNrfvziYgEuOOB7utkd3tTj3M87I6vFZHzy/QdmnL1j69XsTQ1g2ev6EB8VC1vh2NMpVXaBEUWsERE3nALqL0sIi+XZ2Cm7JyXFMNvIWcTnrGGYf94hzd/SaGwqMz+HjHGlCNVPecYjw7A9cBJ78Mi4o+TnPhQVYunUe1wvwEs/iZwpzu+FfCcndHIHTveuDHG1BT5Hs8H4HS4K14+V9oOd6NxltoVewZ4QVWbA3uBke74SGCvO/6Cux9uDaGrgDY4y+xeFxHf03o3pkJ9tjCVj37bzG1nJ3B+m/reDseYSq20CYqvgKeA2RyqQbGwnGIyZWzTnmx+oCffFnYnO/cgL0xZx7BXZ7IhPcvboRljTpOqLgBqn2gfcRa3jgNWq+rzHpsmAcWdOG4AJnqM/8Ht5tETyHCXgvwAnCcidd3imOe5Y8YYU1NsEZG73boTnYHvAUQkGPA/2cEi0gi4EPif+1pw2pV+5u5yZD2g4jpBnwED3P2HA+NV9aCqbsCZ4dz9zN+aKU8r0zJ45Mvl9GoWyf3ntfB2OMZUeqVa/GQtRau2EWNmsze7FnfqvQAE52exelshI8bMZuGjg7wbnDHmtIhIDCdfmtEbZ6bFchFZ4o79FXgamCAiI4FNwBXutsnAEA4t67sJQFX3iMg/gfnufk+o6p4yeivGGFMVjASeAAYCV6rqPne8J/B2KY5/EfgLEOq+jgT2qWqB+9qztk9J3R9VLRCRDHf/hsBcj3Mesx6QiIzC6cRE48aNSxGaKS8ZOfnc/sEiwkP8efnqTvj5lva7YWNqrhMmKERkgqpeISLLOcYHYVVtX26RmTKTGFObueudvyXqcIBvA//Kl4V9+FiuYdPuLJpE2jo4YyorEXmFo++/EcBZONOFj0tVZwLHKxE+4Bj7K3Dncc71FvDWyeI1xpjqSFV3ArcdY3yaiKSc6FgRGQrsVNWFItK/fCI8LKY3gTcBunbtamt6vaSoSPnzhCWk7cvhk1t7Eh0a6O2QjKkSTjaDovjD79DyDsSUnyu7xbE8NYOsvELy8GNmYVvu9vuKXnmrufbZO+ncvj23nZ1AUoMwb4dqjDnakS2dFdgN3Od+YDbGGFMBRKQXzoyFX1R1p4i0Bx4C+nJ4nZ4j9QaGicgQIAgIA17CaeXs586i8KztU1z3J1VE/IA6OPd9qwdUhYyZkcLU1Tt5/KIkujSJ8HY4xlQZJ5xn5NGG7g5V3eT5AO4o//BMWRjQOgZfH+dL1ByCeKhgFA9yD50DU5kS8jd09TcMeflXbnp7HvM32qxtYyoTd4ndUpxixfNU9T1V/daSE8YYU3FE5D84s8guA74VkSeBH3FaNyee6FhVfVhVG6lqU5wilz+r6rXANGCEu9uR9YCK6wSNcPdXd/wqt8tHvHvdeWX0Fk0Zmrkuned+XMuwDg244aym3g7HmCqltA14BwEPHjF2wTHGTCUUFuTPsseP7ER1Iey+keDPbuL5wAW0jLuSt2Zv4vKxc+japC6390/g3Fb1cGoyGWO8RUQexakjsRD4t4j8n6r+18thGWNMTXMh0ElVc91iwVuAtqq68QzO+SAw3k12LMYpaoz7830RSQb24CQ1UNWVIjIBWAUUAHeqauEZXN+Ug7R9OdwzfjHN69Xm6cva2WdpY07RyWpQ3I4zU6KZiCzz2BQKzCrPwEwFiEyAkVPwz8virpAIRnYM5vtFKTy7MJeR7y6gVf1Qbu+fwIXtYq2ojzHecxXQUVWzRSQSp3K8JSiMMaZi5apqLoCq7hWRdaeTnFDV6cB09/l6jtGFw73O5cc5/imcznqmEjpYUMjtHy4ir6CIsdd1ISSgtN8FG2OKnez/mo+A74D/w1ljV2y/VXCvJvwCnQcQPPVhLkn+mYuGPMsk7ceY6SmMHr+EZ39cy6h+CVzepRFB/tZu25gKdlBVswFUdbeIWLbQGGMqXjMRmeTxOt7ztaoO80JMppL55zerWLplH2Ov60yz6BN2AjfGHMfJEhS+QCbHqOouIhGWpKhmBj8DX/wRv4m3c2mHq7n4jv8wNSWL16en8OhXK3hp6jpu7tOU63o2ISzopC2/jTFlw/NDsQAJ9qHYGGMq3PAjXj/nlShMpfXFolQ+mLuZW/s1Y3DbWG+HY0yVdbIExUIOtbc7cgGVAs3KPCLjPXUawg1fw4x/w4xn8Emdz3lXf8KgO85i7vo9jJmRwr+/X8uYaSlc16sJN/eOt5ZJxpS/Iz8UP+uVKIwxpgZT1RnejsFUXqu3ZfLXL5fTs1kED5zf0tvhGFOlnTBBoarxFRWIqSR8fOGch6FpH/j5SagdjYjQKyGSXgmRrNiawZjpKYydkcK4mRu4omsjbu2XQFxEiLcjN6a6WgVEq+oqz0ERSQJ2eSckY4wxxgBk5ORz2wcLCQvy55WrO1vdNmPO0MmKZHY+0XZVXVS24ZhKI74v3Pw9iEDBQSdZ0edPtG0YwWvXdmZDehZvzEjhk/lb+HjeFoa2j+X2/gm0qh/m7ciNqW5eAV4/xngk8DfgmooNxxhjjDEARUXKnycsZeveHMaP6mkzi40pAydb4nGi9XUKnFuGsZjKprgt0pbfYO4YWPklXDYOGvcgPqoWT1/WnnsHtmDczPV89NtmJi5J49xW9bijfwJdm0Z4N3Zjqo/mqvrLkYOq+quIjPFGQMYYU1OJSFBxNw+PsShVTfdWTMZ7xv6SwtTVO/j70CT77GtMGTnhHCRVPecED0tO1BTx/WDkD87yj7cvgF+fg6IiAOrXCeKRC5OY9dC53DeoBYs372XE2DlcPnY209bsRFVPcnJjzEmEnmCbVas1xpiKNV9Eeha/EJHLgNlejMd4yazkdJ79YS1D28dyU++m3g7HmGqj1M15RaQtkAQEFY+p6nvlEZSphBp2gVt/ga/vhZ+egMxtcOGhWn3hIQHcMyCRW/rG88n8Lfz3l/Xc9M58WtUP5fb+CVzYLtbW5BlzepJFZIiqTvYcFJELgPVeiskYY2qqa4C3RGQ60ABnuZ19aVfDbMvI4Z6PF5MQXZtnLmuPyJG9BIwxp6tUCQoReQzoj5OgmAxcAMwELEFRkwTVgRFvQcI5ENfDGSsqAp9DiYeQAD9u6h3PdT2bMHFJGmNnpDB6/BKe+/F3RvVrxogujQjy9/XSGzCmSroX+FZErsDprATQFegFDPVWUMYYUxOp6nIReQp4H9gP9FPVVC+HZSpQXkERd3y4iNz8QsZc14VagaX+vtcYUwql/Up7BDAA2K6qNwEdgDrlFpWpvESg8x8guiWowle3w5THoDD/sN38fX0Y0aURP97bjzeu70LdWgH87asV9HlmGmOmp7A/N/84FzDGeFLVdUA7YAbQ1H3MANqr6u/ei8wYY2oeERmHkzhuD9wEfCMid3o1KFOhnvx2FYs37+M/l3egeb3a3g7HmGqntCm/HFUtEpECEQkDdgJxZ3JhEfEFFgBbVXWoiMQD43Gmyi0ErlfVPBEJxJmp0QXYDVypqhvP5NqmjBQVgn8QzHoRNs1yCmjWbXLYLj4+wvlt6nNeUgxz1u9mzPQUnvl+Da9PT+b6nk24qXe8VTw25iRU9SDwtrfjMMYYw3LgFnWKbG0QkR7A816OyVSQrxZv5b05m/hj33iGtIv1djjGVEulnUGxQETCgf/iJA8WAXPO8NqjgdUer58BXlDV5sBeYKQ7PhLY646/4O5nKgNfP7joJRjxNuxaC2P7wqqJx9xVRDgrIYr3R/bg67v60DcxijEzUujzzM88+tUKtuzJruDgjTHGGGNOjaq+qB4VwFU1Q1VHnugYUz2s2Z7JQ18so3t8BA8ObuXtcIyptkqVoFDVO1R1n6qOBQYBN7hLPU6LiDQCLgT+574WnAJDn7m7vAtc7D4f7r7G3T5ArBJN5dL2UqeAZmQCTLoHcvaecPd2jerw+rVdmHrf2VzcsSHj52+m/7PTuXf8YtZu319BQRtjjDHGnBoRSRSRz0RklYisL354Oy5TvjJz87nt/YWEBfnz6jWdrPC7MeWotEUy3wd+AX5V1TVlcN0Xgb9wqH1eJLBPVQvc16lAQ/d5Q2ALgKoWiEiGu/9h/aZFZBQwCqBx48ZlEKI5JRHxcPMPkP47BNd1imdmbIa6TY97SEJ0bZ4Z0Z4/DWrB/35dz0fzNvPVkjQGtKrHHeck0KWJ9ZM2xhhjTKXyNvAYzqzec3DqUNhfq9WYqnL/hKVs2ZvD+FE9qRcadPKDjDGnrbQ31LeAWOAVN1P8uYiMPp0LishQYKeqLjzpzqdAVd9U1a6q2jU6OrosT21Kyy8A6rd1ns97E17vBYved4ppnkD9OkH8bWgSsx48lz8NbMGizXu5bMwcrnhjDtPW7kRPcrwx1ZmILBeRZcd4LBeRZaU4/i0R2SkiKzzGHheRrSKyxH0M8dj2sIgki8haETnfY3ywO5YsIg+V/Ts1xpgqIVhVfwJEVTep6uM4s4JNNfXGL+v5cdUOHr6gFd2a2pdnxpS3Us2gUNVpIvIL0A0nW3wb0AZ46TSu2RsY5n4gDgLC3POEi4ifO4uiEbDV3X8rTkHOVBHxw+kesvs0rmsqUtJwWPMNTLoLNsyAoS9AYOgJD6lbK4DRAxP5Y794xs/bwn9/Xc9Nb8+ndWwYt/dPYEjb+jalztREZ9pK9B3gVY5uC/2Cqj7rOSAiScBVOPf3BsBUEWnhbn4NZ4lfKjBfRCap6qozjM0YY6qagyLiA6wTkbtwPqdaK4dqanZKOv/+fg0Xto9lZJ94b4djTI1Qqr/2ROQnYBZwJbAW6Kaqp1UdRlUfVtVGqtoU54Pwz6p6LTANp50pwA1AcbXFSe5r3O0/q32lXvmFxcIfJsI5j8CKz+GNfrBtaakODQnw4+Y+8cx44Bz+M6I9eQWF3PPxYgY8P4MPf9tEbn5hOQdvTOXhfkN33Ecpjv8F2FPKyw0HxqvqQVXdACQD3d1HsqquV9U8nI5Lw0/zLRljTFU2GggB7sHpMHc9hz6nmmpke0Yu93y8mPioWjxzWXusBJ4xFaO0X0cvA/KAtjh9n9uKSHAZx/IgcJ+IJOPUmBjnjo8DIt3x+wCbWlxV+PjC2X+BG7+FwgI4eGoFMAP8fLi8axxT/nQ2Y6/rQniwP498uYK+/57GGzNS2J+bX06BG1P5iEhPEZkvIgdEJE9ECkUk8wxOeZe7VOQtEanrjpXU/HEV1wM63vix4hwlIgtEZMGuXbvOIDxjjKl8VHW+qh5Q1VRVvUlVL1XVuSc6RkSCRGSeiCwVkZUi8g93PF5EfnOXzn0iIgHueKD7Otnd3tTjXMdchmfKVl5BEXd8uJCcvELeuL4LtQNLNencGFMGStvF40+q2g+4FGd5xdvAvjO9uKpOV9Wh7vP1qtpdVZur6uWqetAdz3VfN3e3W6XkqqbJWXD3Qmjax3m9bAJkl/YLXfDxEQa3rc9Xd/bmw1t60DImlP/7bg29n/6ZZ39YS/qBg+UUuDGVyqvA1cA6IBi4BWfZxekYAyQAHYFtwHNlEB9g9YCMMdWbiHQVkS9FZJFnXaCTHHYQOFdVO+DcdweLSE/gGZzlds2BvUBxu9KRwF53/AV3vyOX4Q0GXhcR3zJ+iwb41+TVLNq8j3+P6EDzeideomyMKVul7eJxF9AXZyrbRpyimb+WX1im2vELcH5mboNJd0NwBFz2P2jau9SnEBF6N4+id/Molm7Zx9gZKbw2PZn//rqeq7rFcUvfZsRFhJTTGzDG+1Q1WUR8VbUQeFtEFgMPn8Z5dhQ/F5H/At+4L4tr/hTzrAd0vHFjjKlJPgQeAJYDRaU5wF2afMB96e8+FDgXuMYdfxd4HCeBPNx9DvAZ8Ko46wtKluEBG9zZxd2BOWf0jsxhJi7ZyjuzNzKyTzwXto/1djjG1Dilna8UBDwPLPRoBWrMqQuLddqRfnYTvDsUzn4I+t3vLAc5BR3iwhlzXReSdx7gzV9S+GjeZj74bTPDOzTgtv4JtIixbLepdrLd6b9LROTfODMfTqtqrIjEquo29+UlQHGHj0nARyLyPE6RzERgHiBAoojE4yQmruLQh2pjjKlJdqnqpFM9yJ3psBBojjP7LQXY5/G52nPpXMmyOlUtEJEMnOXPDQHP5STHXG4nIqOAUQCNGzc+1VBrtLXb9/PQ58vp1rQuD11wWuX2jDFnqLRdPJ49+V7GlFKDjnDrL/DNfTD9X5A6D679DE6j+FDzerX594gO3DuwBeNmbuCj3zbzxeKtDGwdw+39E+jSpO7JT2JM1XA9TkLiLuBPODMaLj3ZQSLyMdAfiBKRVOAxoL+IdMT5Bm8jcCuAqq4UkQnAKqAAuNOdrVE8k+4HwBd4S1VXluF7M8aYquIxEfkf8BPO0g0AVPWLEx3k3ks7ikg48CVQbn/9quqbwJsAXbt2tcLypbQ/N5/bP1hI7SA/XrumM/7WOc4Yr7CKL8Y7AkPh0jch4RwoyD2t5ISnBuHBPDo0ibvOac47szfy7pyNXDZmBz3iI7i9fwJnt4i26sumqrtYVV8CcoHiAmujOUm7Z1W9+hjD444xVrz/U8BTxxifDEw+lYCNMaYaugknueDPoSUeCpwwQVFMVfeJyDSgFxAuIn7uLArPpXPFy+1SRcQPqINTA+5Ey/DMGVBVHvh0GZv2ZPPxH3tSLyzI2yEZU2NZatB4jwh0vAa63uy8Xvkl/PAIFOSd9inr1grgT4NaMOvBc/nbha3ZtDubG9+ez9BXZvLNsjQKi+yLBFNlHauN3Y0VHYQxxtRw3dxCwDe4XTxuUtWbT3SAiES7Mydwu+ANAlYD04AR7m43ABPd55M4dM8fAfzs1rGYBFzldvmI59AyPHOG/vvrer5fuZ2HL2hF9/gIb4djTI1mMyhM5ZG2GOa8Cptmw4i3ICL+tE9VK9CPW/o24w+9mvLV4q2MnZHCXR8tpmnkWm49O4FLOzck0M8KX5vKT0Suxqn3EC8inuuew4DSt8MxxhhTFmaLSJKqrjqFY2KBd906FD7ABFX9RkRWAeNF5ElgMYdmt40D3neLYO7BqftzwmV45vTNXb+bZ75fy5B29RnZ5/Q/expjyoY4CdnqpWvXrrpgwQJvh2FOx6qJMPFuQOGiF6HtZWVy2sIi5ceV23l9egrLt2ZQLzSQW/rGc02PJgT7+zJu5npen57CHf0TGNmnGb4+thzElA8RWaiqXU9h/yZAPPB/wEMem/YDyypz4WK7FxtjKqNTvQ8fcexqnDbNG3BqUAhOo472ZRhimbH78IntyMzlwpdnEhbsx6S7+lA70L67NaaiHO9ebP8XmsolaTjEdoTPR8JnN0N4E2h0Wp8hDuPrI1zQLpbBbeszK3k3Y2Yk86/Ja3hp6jqCA3zJOlhATn4RL0xZx8Qlabx6TWfio2qd+fsx5gyp6iZgE9BLRGKAbu6m1ZU5OWGMMdXUYG8HYM5MYZE6X0xNS6F2oC9ZB/P5+I89LDlhTCVh/yeayqduE7jpO1jz7aHkxMEDEFj7jE8tIvRJjKJPYhRLtuzjirGzyTpwaHZkTn4hq7dlMmLMbBY+OuiMr2dMWRGRy4Fngek439i9IiIPqOpnXg3MGGNqEDdpbKqoDelZ3PnhIjakZ5GTX8i+nHwa1Q3Gzzp2GFNp2P+NpnLy9Yc2FzvPd6yEF9vCwnegDJckdYwLp/Mx2pAWKWQdLOBvXy3n+xXbyMjOL7NrGnMG/oZTnO0GVf0D0B141MsxGWOMMVXGiDGzWbM9k5z8Q19Ope3LYcSY2V6MyhjjyWZQmMovJApiO8DXo2H9DKc2RVCdMjn1ld3iWJ6aQVbeoV9UAb4+NIuuzZeLtvLB3M34CLRrWIfezaPo0zyKzk3qEuRvBTZNhfNR1Z0er3djSWZjjDHmhFSVVdsymbpqJzn5hRzZ0K1IoUVMqHeCM8YcxRIUpvILjYHrvoRZL8LPT0LaIqfLR8MuZ3zqAa1jeGziysPGgvx9GH9rT4L9fVmyZR8z16UzKzmdN35xCmkG+fvQrWkEfZpH0bt5FEmxYfhYUU1T/r4XkR+Aj93XVwLfeTEeY4wxplLKKyhi3oY9TFm1namrd7J1Xw4i0CQihLR9OeQVHspS1Arw5YpujbwYrTHGkyUoTNXg4wN974MmvZ0Cmiu/KpMERViQP8seP/+427s1jaBb0wj+NKgF+3PzmbdhDzOTnYTF/323BoC6If6c5c6u6NM8iriIkDOOy5gjqeoDInIp0McdelNVv/RmTMYYY0xlkZGTz/S1O5m6eifT1+5kf24BQf4+9E2MZvSARM5tXY8APx/6PP0zeYWHakz7+ggDWsd4MXJjjCdLUJiqpXEPuO1X8Hc7bGxfDqGxUCuq3C8dGuTPgNYxJb/EdmTmMis5vSRh8e2ybQA0iQwpWQ7Sq1kkdWsFlHtspvoTkWdU9UHgi2OMGWOMMTVO6t5spq7awZTVO/ht/R4KipSo2gEMaRvLoKQYejePIjjg8GW5J/piyhjjfZagMFVPsFvYsqgQJtwAeVlw2X8hvl+FhhETFsSlnRtxaedGqCopuw4wc52TsJi0JI2PftuMCLRt4NSv6JsYRRerX2FO3yDgyGTEBccYM8YYY6olVWXF1kymrNrOlNU7Wb0tE4Dm9WpzS99mDEqKoWNcOL629NaYKssSFKbq8vGFy9+Bz26Cd4fB2X+Bfn8B34r/z1pEaF4vlOb1Qrmxdzz5hUUsS93HzHW7mZWczv9+Xc/YGSkE+jn1K4pnWCQ1CLNfouaEROR24A6gmYgs89gUCszyTlTGGGNMxThYUMiclN1MXb2Dqat2sj0zFx+Brk0ieGRIawYmxRAfVcvbYRpjyoglKEzVFtseRs2AyQ/AjGdgw69w9UeHZll4ib+vD12aRNClSQSjByaSdbCAeRv28KtbcPOZ79fwDBAe4s9ZCZH0aR5Nn+ZRNI60+hXmKB/hFMP8P+Ahj/H9qrrHOyEZY4wx5Wdfdh7T1u5kyqodzFi7i6y8QoL9fenXIor7k1pybqt6RNgSWmOqJUtQmKovsDZcMgaanQ2rv4bAsmlBWpZqBfpxTqt6nNOqHgA7M3OZnbKbmcnpzFyXzuTl2wGIiwgu6Q5yVkKU/fI1qGoGkAFc7e1YjDHGmPKyeXc2U1bvYMqq7czfuJfCIiU6NJBhHRsyKKkeZyVE2TJZY2oAS1CY6qPDVc4DIDMN5v0X+j8EfoHejesY6oUFcXGnhlzcqSGqyvr0rJL6Fd8s3cbH87YgAm0ahJUsB+nWNMJ+MRtjjDGmyiksUsbNdNq139E/gZF9miHAsq0ZTivQVTtZu2M/AC1jQrnt7GYMSqpP+4Z1rJW7MTWMJShM9bR2Msx8HlJ+ghFvQ2SCtyM6LhEhIbo2CdG1ueGsphQUFrFsawaz3ITFWzM38MaM9QT4+dC1Sd2ShEXbhnWsfoUxxhhjKrUN6Vnc+eEiNqRnkZNfyLM//s6Y6SmIwJ6sfHx9hG5N6/Lo0CQGtq5Hk0irJ2FMTWYJClM9dbvFaT/61R3wRj8Y+iK0v9zbUZWKn68PnRvXpXPjutw9wK1fsXFPScLiPz+s5T8/rKVOsFO/ojhh0SQyBBFLWBhjjDGm8hgxZjZ7s/MoUud1XkEReQVFBPj68MKVHTinZT3CQ2xJqzHGYQkKU321uhBunwWf3wJf3AJ5B6DrTd6O6pTVCvTjnJb1OKelU79i1/6DzE5xalfMSk7nuxVO/YqG4W79isQoeidEElm78i1tMcYYY0zNkhhTm7nrj67p3KVJXS7p1MgLERljKjNLUJjqrU4juOEbmPsatL3UGSsqAh8f78Z1BqJDAxnesSHDOzr1KzakZzEr2ZldMXnFNj5ZsAWApNgw+iQ6BTe7N40gOMDqV9REIvIWMBTYqapt3bEI4BOgKbARuEJV94ozBeclYAiQDdyoqovcY24A/uae9klVfbci34cxxpiq6cpucSxPzSArr7BkrFaAL1d0s+SEMeZolqAw1Z+vH/Qe7TwvOAjvDHWKaXa9Gar4kggRoVl0bZpF1+b6Xk79ihVpmcxct4uZyem8M2sjb/6yngBfHzo3CadP8yj6JEbTzupX1CTvAK8C73mMPQT8pKpPi8hD7usHgQuARPfRAxgD9HATGo8BXQEFForIJFXdW2HvwhhjTJU0oHUMj01cediYr48woHWMlyIyxlRmlqAwNUt+NgSGwrf3wfrpMOwVCA73dlRlxs/Xh45x4XSMC+eucxPJzitg/sa9zgyLdek8++PvPPvj74QF+dErIbKkpWl8VC2rX1FNqeovItL0iOHhQH/3+bvAdJwExXDgPVVVYK6IhItIrLvvFFXdAyAiU4DBwMflHb8xxlR1IhKHkySOwUnyvqmqL9WU2WxhQf4se/x8b4dhjKkiLEFhapbgunDtZzDnFfjpCRi7BEa8BXHdvB1ZuQgJ8OPsFtGc3SIagPQDB5mdsruk4OYPK3cA0KBOkFNsMzGKsxKiiA61+hXVXIyqbnOfb8f50AzQENjisV+qO3a88aOIyChgFEDjxo3LMGRjjKmyCoA/q+oiEQnFmYU2BbgRm81mjDGHsQSFqXl8fJwlH016w2c3weQ/wx+nV+m6FKUVVTuQYR0aMKxDA1SVTbuzmZnsFNv8YeV2Pl2YCkCr+qElBTd7xEcQEmC3iupKVVVEtAzP9ybwJkDXrl3L7LzGGFNVuQnhbe7z/SKyGifJa7PZjDHmCPZXh6m5GnWFW3+FnL1OcmLrIpjyd6jfDmLaQv22EN0K/KrnbAIRoWlULZpG1eK6nk0oLFJWbM0oSVi8N2cT/5u5AX9foXPjuiUJi/YN6+DnW/2TOdXcDhGJVdVt7ofene74ViDOY79G7thWDn2ILh6fXgFxGmNMteIuuesE/EY5zmYzxpiqyhIUpmYLDj9UgyI/G/KyYMHbUJDjjPn4wcgp0LAzpCdDxmaIaQe1o70Vcbnx9RE6xIXTIS6cO89pTk5eIQs27WGmW7/iuSm/89yU3wkN9KOnR/2KhGirX1EFTQJuAJ52f070GL9LRMbjTCvOcJMYPwD/EpG67n7nAQ9XcMzGGFOliUht4HPgXlXN9PzdWZaz2WypnTGmKrMEhTHFmvaBUdOgqBB2p8CO5bB9BUQ2d7Yv+wR++bfzvHbMoZkWZz8IASHei7ucBAf40jcxmr6J0XAB7MnKY3aKM7vi13XpTFnl1K+ILa5f0TyKs5pHUi80yMuRG08i8jHO7IcoEUnFWb/8NDBBREYCm4Ar3N0n4xRlS8YpzHYTgKruEZF/AvPd/Z4onmJsjDHm5ETEHyc58aGqfuEOl8tsNltqZ4ypysRZ3la9dO3aVRcsWODtMEx1k7MXti2DHSucxMWO5ZCxFR5IcZaITH4AtsxzlobEtHN/tq1WXUI8bd6dza/Ju5iVnM7slN3sy84HoGVMqFtwM5Ie8ZHUCrQ8qCcRWaiqXb0dR0Wwe7ExpjKq6Puw25XjXWCPqt7rMf4fYLdHkcwIVf2LiFwI3IWTMO4BvKyq3d0imQuBzu4pFgFdTpQwtvuwMaayOt692P5yMKa0gutCs7OdR7GiwkPFNSObQ/rvsPZ7WPyBMxaRAPcscp4v+Rj8g52ZF3Xjq3xRzsaRIVwb2YRrezj1K1alZZbUr/jgt028NWsDfj5O/YrihEX7RuH4W/0KY4wxNUtv4HpguYgsccf+is1mM8aYo9gMCmPKmirs3+7MtCjIhdYXOeMvtIUMt7ZVQG2olwRtLoFedzhj+bngXz2WR+TmF7Jg496ShMWKtAxUoXagHz2bRdC7eRR9E6NIiK5d4+pX2AwKY4zxLrsPG2OM99kMCmMqigiExToPT3fNh52rPZaIrIDsdGdbQR480wTCGri1LdwlIg27QO16Ff8ezlCQvy99EqPokxgFwN6sPOas312SsJi62llmGxMWWFK/onfzKGLCqkeCxhhjjDHGGHPqKjxBISJxwHs4rZQUeFNVX3LX1X0CNAU2Aleo6l533d5LOFPdsoEbVXVRRcdtzBnzD3a6gTTsfPS2wjzoc59T12LbMljlNlUY8Bj0vQ8O7IJfnztU1yK6VZWabVG3VgBD2sUypJ2TtNmyJ9vpDpKczrQ1O/li0VYAEuvVLpld0aNZJLWtfoUxxhhjjDE1hjc+/RcAf1bVRSISCiwUkSnAjcBPHoWCHgIeBC4AEt1HD2CM+9OY6iOwNvR/8NDrg/thx6pDszD2boBF7zqtUAHEF6JawNDnoclZkJsJ+TkQGnP0uSuhuIgQru7emKu7N6aoSFm1LZNZbsLi43mbeWf2Rvx8hI5x4W79iig6xln9CmOMMcYYY6qzCk9QqOo2YJv7fL+IrAYaAsM51DrpXZy2SQ+64++pUyxjroiEF7dkqujYjakwgaHQ2CMPF9cdHk6FPRsOtT/dsQKCI5ztqyfBxDuhVrQzw6K4k0irIc65KjEfH6Ftwzq0bViHW89OIDe/kEWbDtWvePnndbz00zpqBfjSs1lkScIisV7Nq19hjDHGGGNMdebV+dMi0hToBPwGxHgkHbbjLAEBJ3mxxeOwVHfssASFiIwCRgE0bty4/II2xlt8fCGqufNoc8nh2+J6wvn/59a3WA6/veEsG3kgxUlQLP4ANs5y6lsULxMJifDO+ziJIH9fzmoexVnNnfoV+7LzmJNyqH7FT2uc+hXRoYEltSv6NI+ifp2qs+TFGGOMMcYYczSvJShEpDbwOXCvqmZ6fhOqqioip9ReRFXfBN4Ep2JxWcZqTKVXnLgoVpgPu1OglvNHPvu3QfJUWPrRoX0iEuDuhU5Rz21Lwb8WRDSrdO1Pw0MCuKBdLBd41K+YnZLOzOTdzPh9F18udupXJETXom9iNL2bR9GjWQRhQf7eDNsYY4wxxhhzirySoBARf5zkxIeq+oU7vKN46YaIxAI73fGtQJzH4Y3cMWPM8fj6Q71Wh173e8B57N9xaInIwUwnOQEw+S+wZS74hzjtT+u3hSZ9oP3l3on/BOIiQrgyojFXdnPqV6zeXly/Yjfj5zv1K3x9hA6N6pTMsOjUuC4BfpUr8WKMMcYYY4w5nDe6eAgwDlitqs97bJoE3AA87f6c6DF+l4iMxymOmWH1J4w5TaExzqP5wMPHL3wOti05VNti5Vewf/uhBMW7F0FQnUPtT2PaQnjjQwkOL/HxEdo0qEObBnUY1S+BgwWFLNq0r6Tg5qvTknn552RCAnzpER9RUr+iZUyo1a8wxhhjjDGmkvHGDIrewPXAchFZ4o79FScxMUFERgKbgCvcbZNxWowm47QZvalCozWmJqjvFtYspgp5Wc7zokKnGOf25bD6G5zuwED3UTDkP872JR9CTBtn9oV/cIWHXyzQz5deCZH0Sojk/vNbkpGdz5z1u5nl1q+YtnY1AFG1A+ndPLJkhkWDcO/FbIwxxhhjjHF4o4vHTOB4X10OOMb+CtxZrkEZYw4n4rQ+Bac45xXvOs8PHoCdq5xkRXRLZ2zPBph0t3ucD0Q2d2ZYdB8FTXo5yY7ic1awOiH+DG5bn8Ft6wOwdV+OM7tinfOYuCQNgGbRtUqSFT2bRVIn2OpXGGOMMcYYU9G82sXDGFPFBNZ2Wp7GdT80FtEM7l7kdhBxl4ikLoB2I5ztG2fCpzceWhpSv53zM7qlUyujAjUMD+aKrnFc0TWOoiJl7Y79JctBPl2QyntzNuEj0L5ROH0Ti+tXhBPo51uhcRpjjDHGGFMTWYLCGHNmfHwgMsF5JA0/NF48cyKoDrS8wElczPsvFB50xm/5GRp1gS3znEf9tk6Ni1qRFRS20Do2jNaxYdzStxl5BUUs3ryXmW7C4rVpybzyczLB/r50j48omWHRqn4oCoybuZ7Xp6dwR/8ERvZphq+P1bQwxhhjjDHmTFiCwhhTPoqXdMS2h+GvOs8LC2B3spOsiElyxlJ+hun/d+i40FhnhsXl7zgzNnIzIKC2s9SkHAX4+dCjWSQ9mkXy5/NakpGTz29u/YqZyek8NdmpX1E3xJ/CIiUnv5D8QuWFKeuYuCSNV6/pTHxUrXKN0RhjjDHGmOrMEhTGmIrj6+e0P/Vsgdr/Ieg68lD70x0rYO8mCHD/2J/8AKyaBPVaH5plEdsBGvco11DrBPtzXpv6nNfGqV+R5taveOTLFeQVFpXsl5NfyOptmYwYM5uFjw4q15iMMcYYY4ypzixBYYzxvtrRUPtcSDj36G1tLoWQKCeBsfprWPSe0y3kjjnO9mnu7IviGhd1m5ZLQc4G4cFc3jWOzxelMnf9nsO2FSm0iAkt82saY4wxxhhTk1iCwhhTubUc7DzAqWuRmQbZuw9tXz8dtvxGSfvTwDDodD0M/pfzevsKp5BnQEiZhHNltziWp2aQlVdYMlYrwJcrujUqk/MbY4wxxhhTU1mCwhhTdYhAnYbOo9jIHyAvG3auPrRMJLKZsy0/B97o6zyPSDg0yyLxPKc2xmkY0DqGxyauPGzM10cY0DrmtM7nTSKyEdgPFAIFqtpVRCKAT4CmwEbgClXdKyICvAQMAbKBG1V1kTfiNsYYY4wx1ZMlKIwxVV9AiNMRpFGXw8fFB654z0labF8OWxfCyi/BP9hJUGSkwpe3HWp9Wr+d0/7UL/C4lwoL8mfZ4+eX8xuqUOeoarrH64eAn1T1aRF5yH39IHABkOg+egBj3J/GGGNOQETeAoYCO1W1rTt2yslgEbkB+Jt72idV9d2KfB/GGFMRLEFhjKm+/AKh9UXOo1huxqHnOXshLwsWvAUFuc6Yjx9c9TG0OM9ZTrJrrZO4qBVVsbF7z3Cgv/v8XWA6ToJiOPCeqiowV0TCRSRWVbd5JUpjjKk63gFeBd7zGDulZLCb0HgM6IqzpnGhiExS1b0V9i6MMaYCWILCGFOzBNU59Lx+Oxg1DYoKYXfKoSUixV1Gfv8evvmT87x2/UNLRM66B2pFVnzsZU+BH0VEgTdU9U0gxiPpsB0oXrvSENjicWyqO2YJCmOMOQFV/UVEmh4xfErJYHffKaq6B0BEpgCDgY/LO35jjKlIlqAwxhgfX4hu4TzaXnZovM2lTu2K7cud9qfbV8CGX6Dvfd6LtWz1UdWtIlIPmCIiazw3/n979x/rV13fcfz5WouBVCKwMkKADiVsBg0C67rNOHU6iO4PqZOhJI66LOmyyaIjMzPbHzKdCdnYsiw6lxKbaeLoyATtGBmiYpRsEwTK7yCV1UhlbRyBwRZxtO/98T13fNPce3sLPd/POd/7fCQ393zP95z7ffWTe19t3v2ec6uquuHFiiXZCmwF2LBhw9FLKknz5UiHwUvtl6S54oBCkpZy3AnwqjdNPhYc+F9Yc0yzSEdTVe3tPu9PciOwCdi3cOlG9792+7vD9wJnTJ1+erfv0K+5DdgGsHHjxiMabkjSavRihsHLcVAsacx+rHUASRqVORlOJFmX5PiFbeAi4AFgJ7ClO2wL8MVueydweSZ+Hnja+09I0ou2rxsCs8Jh8IqGxDAZFFfVxqraePLJJx/14JLUJwcUkrQ6nQLcnuRe4A7gn6rqn4GrgQuTPAr8cvcY4GbgMWA3cC3wO7OPLElz40iHwbcAFyU5McmJTIbKt8w6tCT1zUs8JGkVqqrHgNctsv8/gbcusr+A988gmiTNlSTXMbnJ5fokjzP5bRxXA9cn+U3gu8Cl3eE3M/kVo7uZ/JrR3wCoqieTfAy4szvuows3zJSkeeKAQpIkSepJVV22xFNHNAyuqu3A9qMYTZIGx0s8JEmSJElScw4oJEmSJElScw4oJEmSJElScw4oJEmSJElScw4oJEmSJElScw4oJEmSJElScw4oJEmSJElScw4oJEmSJElScw4oJEmSJElScw4oJEmSJElScw4oJEmSJElScw4oJEmSJElScw4oJEmSJElScw4oJEmSJElScw4oJEmSJElScw4oJEmSJElScw4oJEmSJElScw4oJEmSJElSc6MZUCR5W5JHkuxO8uHWeSRptbGHJak9u1jSPBvFgCLJGuCTwNuBc4DLkpzTNpUkrR72sCS1ZxdLmnejGFAAm4DdVfVYVf0I2AFc3DiTJK0m9rAktWcXS5pra1sHWKHTgO9NPX4c+LnpA5JsBbZ2D59L8sCMsh0t64EftA5xBMzbL/P2r1Xmn2zwmkfDYXsYRt/FY/s+Nm//xpbZvCsz1h4G/008RObtl3n7N6guHsuA4rCqahuwDSDJt6pqY+NIR2Rsmc3bL/P2b4yZx2DMXWzefo0tL4wvs3kF4+5hGF9m8/bLvP0bWuaxXOKxFzhj6vHp3T5J0mzYw5LUnl0saa6NZUBxJ3B2klcmeRnwHmBn40yStJrYw5LUnl0saa6N4hKPqno+yRXALcAaYHtVPbjMKdtmk+yoGltm8/bLvP0bY+ZmXkQPw/jW2Lz9GlteGF9m8845/008SObtl3n7N6jMqarWGSRJkiRJ0io3lks8JEmSJEnSHHNAIUmSJEmSmpu7AUWStyV5JMnuJB9unedwkuxJcn+SXUm+1TrPYpJsT7J/+vdoJzkpya1JHu0+n9gy47Ql8l6VZG+3zruS/ErLjNOSnJHktiQPJXkwyQe6/YNc42XyDnKNkxyb5I4k93Z5/7jb/8ok3+y64u+7m43pKBhbD8Pwu9ge7pc93D+7ePbG1sVD72Gwi/tmF/drLD08V/egSLIG+DZwIfA4kzsdX1ZVDzUNtowke4CNVfWD1lmWkuSNwLPAZ6vqtd2+PwWerKqru7/0TqyqP2iZc8ESea8Cnq2qa1pmW0ySU4FTq+ruJMcDdwGbgfcxwDVeJu+lDHCNkwRYV1XPJjkGuB34AHAlcENV7UjyN8C9VfWpllnnwRh7GIbfxfZwv+zh/tnFszXGLh56D4Nd3De7uF9j6eF5ewfFJmB3VT1WVT8CdgAXN840elX1deDJQ3ZfDHym2/4Mkx/GQVgi72BV1RNVdXe3/QzwMHAaA13jZfIOUk082z08pvso4C3AP3T7B7O+c8Ae7oE93C97uH928czZxT2wi/tlF/drLD08bwOK04DvTT1+nAF/k3QK+FKSu5JsbR3mCJxSVU902/8BnNIyzApdkeS+7u1ug3hr2KGSnAmcD3yTEazxIXlhoGucZE2SXcB+4FbgO8BTVfV8d8gYumIsxtjDMM4uHnxHLGKQHTHNHu6PXTxTY+ziMfYwjKAnFjHYnlhgF/djDD08bwOKMXpDVV0AvB14f/dWrFGpyXVCQ79W6FPAWcB5wBPAnzdNs4gkLwc+D3ywqv5r+rkhrvEieQe7xlV1oKrOA05n8r9Kr26bSAM06i4eYkcsYrAdscAe7pddrMMYdQ/DMHtiEYPuCbCL+zSGHp63AcVe4Iypx6d3+warqvZ2n/cDNzL5RhmDfd11VwvXX+1vnGdZVbWv+4E8CFzLwNa5uw7s88DnquqGbvdg13ixvENfY4Cqegq4DfgF4IQka7unBt8VIzK6HobRdvFgO2IxQ+8Ie3h27OKZGF0Xj7SHYcA9sZih94RdPBtD7uF5G1DcCZzd3Yn0ZcB7gJ2NMy0pybruhiokWQdcBDyw/FmDsRPY0m1vAb7YMMthLZRa550MaJ27G9Z8Gni4qv5i6qlBrvFSeYe6xklOTnJCt30ckxuGPcyklC/pDhvM+s6BUfUwjLqLB9kRSxlqR4A9PAt28cyNqotH3MMw0J5YysB7wi7u0Vh6eK5+iwdAJr/G5S+BNcD2qvp420RLS/IqJhNigLXA3w0xb5LrgDcD64F9wEeALwDXAxuA7wKXVtUgbsKzRN43M3mbVQF7gN+aupatqSRvAL4B3A8c7Hb/IZNr2Aa3xsvkvYwBrnGSc5nc8GcNk6Hs9VX10e7nbwdwEnAP8N6qeq5d0vkxph6GcXSxPdwve7h/dvHsjamLx9DDYBf3zS7u11h6eO4GFJIkSZIkaXzm7RIPSZIkSZI0Qg4oJEmSJElScw4oJEmSJElScw4oJEmSJElScw4oJEmSJElScw4opE6SzUnOmXr8tSQbZ/C6f5vkksMfKUnzzy6WpLbsYbXkgEJ6wWbgnMMdNC3J2n6iSNKqtRm7WJJa2ow9rEYcUGjwkpyZ5OEk1yZ5MMmXkhzXPff/E90k65Ps6bbfl+QLSW5NsifJFUmuTHJPkn9LctIhr/F64B3AnyXZleSs7qlfS3JHkm8n+cWpr70zyVeBryRZl2R7d9w9SS6eyv2NJHd3H6/v9ifJJ5I8kuTLwE9M5bg6yUNJ7ktyTZ/rKklHwi6WpLbsYa0GDig0FmcDn6yq1wBPAe9awTmvBX4V+Fng48D/VNX5wL8Cl08fWFX/AuwEPlRV51XVd7qn1lbVJuCDwEemTrkAuKSq3gT8EfDV7rhfYlLo64D9wIVVdQHwbuCvunPfCfw0k8n05cBCSf9499xrqupc4E9W8GeUpFmyiyWpLXtYc8234mgs/r2qdnXbdwFnruCc26rqGeCZJE8D/9jtvx84d4Wve8MSr3lrVT3ZbV8EvCPJ73ePjwU2AN8HPpHkPOAA8FPd828ErquqA8D3u6kzwNPAD4FPJ7kJuGmFGSVpVuxiSWrLHtZcc0ChsXhuavsAcFy3/TwvvBPo2GXOOTj1+CAr/95fOOfAIef899R2gHdV1SPTJya5CtgHvK7L+MPlXqiqnk+yCXgrcAlwBfCWFeaUpFmwiyWpLXtYc81LPDR2e4Cf6bZf6l1/nwGOfxHn3QL8bpIAJDm/2/8K4ImqOgj8OrCm2/914N1J1iQ5lclb4EjycuAVVXUz8HtMSlySxmAPdrEktbQHe1hzwAGFxu4a4LeT3AOsf4lfawfwoe6mPmcd9ugXfAw4BrgvyYPdY4C/BrYkuRd4NS9MmG8EHgUeAj7L5Po/mPxFcFOS+4DbgStfyh9GkmbILpaktuxhzYVUVesMkiRJkiRplfMdFJIkSZIkqTkHFJIkSZIkqTkHFJIkSZIkqTkHFJIkSZIkqTkHFJIkSZIkqTkHFJIkSZIkqTkHFJIkSZIkqbn/A/SVTfkNJvbHAAAAAElFTkSuQmCC\n", + "image/png": 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" ] @@ -1030,9 +1030,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "py38arm", "language": "python", - "name": "python3" + "name": "py38arm" }, "language_info": { "codemirror_mode": { @@ -1044,7 +1044,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.12" + "version": "3.8.13" } }, "nbformat": 4, diff --git a/02.basic-benchmarks-seaborn.ipynb b/02.basic-benchmarks-seaborn.ipynb index b38c469..6dff4ee 100644 --- a/02.basic-benchmarks-seaborn.ipynb +++ b/02.basic-benchmarks-seaborn.ipynb @@ -71,16 +71,16 @@ " \n", " \n", " 0\n", - " 1347.0233\n", - " 0:22:27\n", - " 12910.21\n", - " 15135.63\n", - " 13073.72\n", - " 13073.72\n", - " 0.01\n", - " 0.14\n", - " 2762.7\n", - " 37225.36\n", + " 8046.1403\n", + " 2:14:06\n", + " 10401.48\n", + " 58493.38\n", + " 10403.37\n", + " 10403.95\n", + " 72282.79\n", + " 7.61\n", + " 378.65\n", + " 30478.66\n", " 100\n", " 10000\n", " \n", @@ -89,11 +89,11 @@ "" ], "text/plain": [ - " s h:m:s max_rss max_vms max_uss max_pss io_in io_out \\\n", - "0 1347.0233 0:22:27 12910.21 15135.63 13073.72 13073.72 0.01 0.14 \n", + " s h:m:s max_rss max_vms max_uss max_pss io_in \\\n", + "0 8046.1403 2:14:06 10401.48 58493.38 10403.37 10403.95 72282.79 \n", "\n", - " mean_load cpu_time n_query n_against \n", - "0 2762.7 37225.36 100 10000 " + " io_out mean_load cpu_time n_query n_against \n", + "0 7.61 378.65 30478.66 100 10000 " ] }, "execution_count": 2, @@ -156,136 +156,136 @@ " \n", " \n", " 0\n", - " 1347.0233\n", - " 0:22:27\n", - " 12910.21\n", - " 15135.63\n", - " 13073.72\n", - " 13073.72\n", - " 0.01\n", - " 0.14\n", - " 2762.70\n", - " 37225.36\n", + " 8046.1403\n", + " 2:14:06\n", + " 10401.48\n", + " 58493.38\n", + " 10403.37\n", + " 10403.95\n", + " 72282.79\n", + " 7.61\n", + " 378.65\n", + " 30478.66\n", " 100\n", " 10000\n", " \n", " \n", " 0\n", - " 1291.4875\n", - " 0:21:31\n", - " 14541.96\n", - " 18260.40\n", - " 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0:22:27 12910.21 15135.63 13073.72 13073.72 0.01 \n", - "0 1291.4875 0:21:31 14541.96 18260.40 14601.04 14601.05 0.01 \n", - "0 1454.4474 0:24:14 16348.15 18954.26 16429.44 16429.44 0.02 \n", - "0 1551.7362 0:25:51 14438.77 16864.46 14666.07 14666.08 0.02 \n", - "0 1603.6622 0:26:43 18893.50 21000.83 18968.33 18968.33 0.03 \n", - "0 1696.6006 0:28:16 17783.73 19868.45 17888.35 17888.35 0.03 \n", - "0 1610.4366 0:26:50 16855.73 19042.42 16989.04 16989.04 0.04 \n", - "0 1770.2948 0:29:30 16316.45 19000.11 16440.92 16440.92 0.04 \n", - "0 1806.3763 0:30:06 16779.61 19569.78 16286.82 16286.82 95967.58 \n", + "0 8046.1403 2:14:06 10401.48 58493.38 10403.37 10403.95 72282.79 \n", + "0 6634.0672 1:50:34 10220.22 55552.64 10231.77 10232.34 60197.02 \n", + "0 6791.2807 1:53:11 10283.14 50499.57 10275.11 10275.26 57833.04 \n", + "0 5399.0796 1:29:59 10114.58 46904.75 10116.12 10116.37 47400.44 \n", + "0 7236.9012 2:00:36 10306.49 58546.62 10235.79 10236.42 64539.15 \n", + "0 8307.0373 2:18:27 10262.73 54648.19 10253.57 10254.16 69524.23 \n", + "0 5935.0510 1:38:55 10436.12 51007.27 10450.90 10451.52 54838.95 \n", + "0 6634.9251 1:50:34 10577.44 45540.72 10551.79 10552.37 57337.78 \n", + "0 6092.0311 1:41:32 10244.95 45939.66 10276.76 10277.33 52401.86 \n", "\n", " io_out mean_load cpu_time n_query n_against \n", - "0 0.14 2762.70 37225.36 100 10000 \n", - "0 0.24 3044.57 39323.17 200 10000 \n", - "0 0.31 2828.24 41136.09 300 10000 \n", - "0 0.40 2751.87 42702.26 400 10000 \n", - "0 0.48 2802.76 44947.46 500 10000 \n", - "0 0.59 2755.67 46753.81 600 10000 \n", - "0 0.70 3032.36 48835.22 700 10000 \n", - "0 0.85 2863.60 50694.71 800 10000 \n", - "0 0.97 2889.70 52198.87 900 10000 " + "0 7.61 378.65 30478.66 100 10000 \n", + "0 16.52 454.59 30161.81 200 10000 \n", + "0 23.31 448.54 30472.00 300 10000 \n", + "0 29.00 562.59 30399.56 400 10000 \n", + "0 35.26 446.27 32299.50 500 10000 \n", + "0 42.31 404.21 33580.93 600 10000 \n", + "0 50.85 562.69 33401.60 700 10000 \n", + "0 58.04 527.36 34999.19 800 10000 \n", + "0 66.00 595.16 36253.98 900 10000 " ] }, "execution_count": 3, @@ -373,136 +373,136 @@ " \n", " \n", " 0\n", - " 154.1568\n", - " 0:02:34\n", - " 8026.29\n", - " 8707.47\n", - " 8042.18\n", - " 8042.25\n", - " 0.07\n", - " 0.11\n", - " 2112.52\n", - " 3256.75\n", + " 190.5965\n", + " 0:03:10\n", + " 7835.11\n", + " 13411.27\n", + " 7682.85\n", + " 7684.71\n", + " 23.64\n", + " 6.94\n", + " 1537.50\n", + " 2934.33\n", " 1000\n", " 1000\n", " \n", " \n", " 0\n", - " 269.0769\n", - " 0:04:29\n", - " 8977.02\n", - " 9920.71\n", - " 8961.81\n", - " 8961.88\n", - " 0.13\n", - " 0.25\n", - " 2450.90\n", - " 6594.63\n", + " 492.1393\n", + " 0:08:12\n", + " 9266.73\n", + " 19072.92\n", + " 9177.62\n", + " 9178.36\n", + " 2893.39\n", + " 14.18\n", + " 1306.44\n", + " 6433.30\n", " 1000\n", " 2000\n", " \n", " \n", " 0\n", - " 354.2737\n", - " 0:05:54\n", - " 11786.54\n", - " 13038.87\n", - " 11863.02\n", - " 11863.11\n", - " 0.20\n", - " 0.36\n", - " 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0.00\n", + " 565.28\n", + " 29627.37\n", " 1000\n", " 8000\n", " \n", " \n", " 0\n", - " 1576.3652\n", - " 0:26:16\n", - " 16715.54\n", - " 19374.40\n", - " 16759.83\n", - " 16759.83\n", - " 7.45\n", - " 1.00\n", - " 3052.70\n", - " 48122.82\n", + " 5638.5937\n", + " 1:33:58\n", + " 10485.32\n", + " 43337.22\n", + " 10510.07\n", + " 10510.71\n", + " 49704.38\n", + " 66.75\n", + " 577.80\n", + " 32585.03\n", " 1000\n", " 9000\n", " \n", @@ -511,27 +511,27 @@ "" ], "text/plain": [ - " s h:m:s max_rss max_vms max_uss max_pss io_in io_out \\\n", - "0 154.1568 0:02:34 8026.29 8707.47 8042.18 8042.25 0.07 0.11 \n", - "0 269.0769 0:04:29 8977.02 9920.71 8961.81 8961.88 0.13 0.25 \n", - "0 354.2737 0:05:54 11786.54 13038.87 11863.02 11863.11 0.20 0.36 \n", - "0 478.0915 0:07:58 13964.38 15485.38 14074.45 14074.53 0.26 0.48 \n", - "0 704.6193 0:11:44 15294.20 18001.37 15028.22 15028.30 0.33 0.64 \n", - "0 1073.2904 0:17:53 12150.98 14048.74 12201.99 12201.99 0.39 0.73 \n", - "0 1269.1121 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6594.63 1000 2000 \n", - "0 2943.38 10428.58 1000 3000 \n", - "0 3003.24 14358.91 1000 4000 \n", - "0 2722.32 19182.34 1000 5000 \n", - "0 2635.62 28288.41 1000 6000 \n", - "0 2923.52 37104.07 1000 7000 \n", - "0 3018.64 42844.40 1000 8000 \n", - "0 3052.70 48122.82 1000 9000 " + " io_out mean_load cpu_time n_query n_against \n", + "0 6.94 1537.50 2934.33 1000 1000 \n", + "0 14.18 1306.44 6433.30 1000 2000 \n", + "0 21.63 2495.44 8417.19 1000 3000 \n", + "0 28.87 762.82 13863.96 1000 4000 \n", + "0 36.60 447.18 19284.64 1000 5000 \n", + "0 43.01 2918.98 18401.39 1000 6000 \n", + "0 51.11 578.58 25962.25 1000 7000 \n", + "0 0.00 565.28 29627.37 1000 8000 \n", + "0 66.75 577.80 32585.03 1000 9000 " ] }, "execution_count": 4, @@ -593,119 +593,119 @@ " \n", " \n", " 0\n", - " 1347.0233\n", - " 0:22:27\n", - " 12910.21\n", - " 15135.63\n", - " 13073.72\n", - " 13073.72\n", - " 0.01\n", - " 0.14\n", - " 2762.70\n", - " 37225.36\n", + " 8046.1403\n", + " 2:14:06\n", + " 10401.48\n", + " 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h:m:s max_rss max_vms max_uss max_pss io_in io_out \\\n", - "0 1347.0233 0:22:27 12910.21 15135.63 13073.72 13073.72 0.01 0.14 \n", - "0 1291.4875 0:21:31 14541.96 18260.40 14601.04 14601.05 0.01 0.24 \n", - "0 1454.4474 0:24:14 16348.15 18954.26 16429.44 16429.44 0.02 0.31 \n", - "0 1551.7362 0:25:51 14438.77 16864.46 14666.07 14666.08 0.02 0.40 \n", - "0 1603.6622 0:26:43 18893.50 21000.83 18968.33 18968.33 0.03 0.48 \n", + " s h:m:s max_rss max_vms max_uss max_pss io_in \\\n", + "0 8046.1403 2:14:06 10401.48 58493.38 10403.37 10403.95 72282.79 \n", + "0 6634.0672 1:50:34 10220.22 55552.64 10231.77 10232.34 60197.02 \n", + "0 6791.2807 1:53:11 10283.14 50499.57 10275.11 10275.26 57833.04 \n", + "0 5399.0796 1:29:59 10114.58 46904.75 10116.12 10116.37 47400.44 \n", + "0 7236.9012 2:00:36 10306.49 58546.62 10235.79 10236.42 64539.15 \n", "\n", - " mean_load cpu_time n_query n_against bench_type varied_n \\\n", - "0 2762.70 37225.36 100 10000 vary_n_queries 100 \n", - "0 3044.57 39323.17 200 10000 vary_n_queries 200 \n", - "0 2828.24 41136.09 300 10000 vary_n_queries 300 \n", - "0 2751.87 42702.26 400 10000 vary_n_queries 400 \n", - "0 2802.76 44947.46 500 10000 vary_n_queries 500 \n", + " io_out mean_load cpu_time n_query n_against bench_type varied_n \\\n", + "0 7.61 378.65 30478.66 100 10000 vary_n_queries 100 \n", + "0 16.52 454.59 30161.81 200 10000 vary_n_queries 200 \n", + "0 23.31 448.54 30472.00 300 10000 vary_n_queries 300 \n", + "0 29.00 562.59 30399.56 400 10000 vary_n_queries 400 \n", + "0 35.26 446.27 32299.50 500 10000 vary_n_queries 500 \n", "\n", - " min \n", - "0 22.450388 \n", - "0 21.524792 \n", - "0 24.240790 \n", - "0 25.862270 \n", - "0 26.727703 " + " min \n", + "0 134.102338 \n", + "0 110.567787 \n", + "0 113.188012 \n", + "0 89.984660 \n", + "0 120.615020 " ] }, "execution_count": 5, @@ -727,13 +727,13 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 19, "id": "cf9eb64f", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -748,7 +748,7 @@ "g = sns.relplot(data=benchD, x='varied_n', y='min', col=\"bench_type\", \\\n", " markers=True,marker=\"o\",\\\n", " kind='line', facet_kws=dict(sharex=False))\n", - "g.set(ylim=(0, 35))\n", + "#g.set(ylim=(0, 35))\n", "\n", "titles = [\"varying number of queries (10k subjects)\", 'varying number of subjects (1000 queries)']\n", "x_labels = ['num queries', 'num subject datasets']\n", @@ -764,7 +764,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 18, "id": "d8560759", "metadata": {}, "outputs": [ @@ -778,7 +778,7 @@ }, { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -791,7 +791,7 @@ "# linear regression version\n", "g = sns.lmplot(data=benchD, x='varied_n', y='min', col=\"bench_type\",\n", " markers=\"o\",sharex=False, scatter_kws={\"s\": 30}) \n", - "g.set(ylim=(0, 35))\n", + "#g.set(ylim=(0, 35))\n", "\n", "titles = [\"varying number of queries (10k subjects)\", 'varying number of subjects (1000 queries)']\n", "x_labels = ['Number of Queries', 'Number of Subject Datasets']\n", @@ -853,72 +853,72 @@ " \n", " \n", " 0\n", - " 1394.1251\n", - " 0:23:14\n", - " 16106.77\n", - " 18410.19\n", - " 16167.91\n", - " 16167.94\n", - " 95974.41\n", - " 1.14\n", - " 2914.11\n", - " 40626.79\n", + " 6410.4036\n", + " 1:46:50\n", + " 10456.73\n", + " 46762.75\n", + " 10474.48\n", + " 10474.75\n", + " 54614.34\n", + " 73.48\n", + " 586.18\n", + " 37592.65\n", " a\n", " \n", " \n", " 0\n", - " 1394.1750\n", - " 0:23:14\n", - " 17553.49\n", - " 20057.43\n", - " 17685.95\n", - " 17685.99\n", - " 94003.57\n", - " 1.16\n", - " 2771.80\n", - " 38643.81\n", + " 10972.9724\n", + " 3:02:52\n", + " 10129.77\n", + " 56932.70\n", + " 10109.43\n", + " 10110.02\n", + " 84926.57\n", + " 72.73\n", + " 331.31\n", + " 36359.01\n", " b\n", " \n", " \n", " 0\n", - " 1357.7237\n", - " 0:22:37\n", - " 18257.87\n", - " 20041.38\n", - " 18277.77\n", - " 18277.80\n", - " 91280.15\n", - " 1.01\n", - " 2794.07\n", - " 37936.37\n", + " 6546.8879\n", + " 1:49:06\n", + " 10403.43\n", + " 52091.42\n", + " 10226.46\n", + " 10227.06\n", + " 59158.95\n", + " 73.10\n", + " 530.59\n", + " 34751.04\n", " c\n", " \n", " \n", " 0\n", - " 1505.0091\n", - " 0:25:05\n", - " 16107.48\n", - " 19187.17\n", - " 16137.28\n", - " 16137.32\n", - " 93738.74\n", - " 1.02\n", - " 2605.24\n", - " 39209.39\n", + " 8474.0678\n", + " 2:21:14\n", + " 10509.81\n", + " 55628.16\n", + " 10474.58\n", + " 10475.17\n", + " 74463.39\n", + " 72.83\n", + " 430.85\n", + " 36527.69\n", " d\n", " \n", " \n", " 0\n", - " 1596.4828\n", - " 0:26:36\n", - " 14046.44\n", - " 15868.38\n", - " 14061.43\n", - " 14061.46\n", - " 91948.11\n", - " 0.96\n", - " 2367.13\n", - " 37791.57\n", + " 6643.4003\n", + " 1:50:43\n", + " 10399.51\n", + " 47443.64\n", + " 10452.64\n", + " 10453.31\n", + " 57368.30\n", + " 76.80\n", + " 530.69\n", + " 35255.88\n", " e\n", " \n", " \n", @@ -926,19 +926,19 @@ "" ], "text/plain": [ - " s h:m:s max_rss max_vms max_uss max_pss io_in \\\n", - "0 1394.1251 0:23:14 16106.77 18410.19 16167.91 16167.94 95974.41 \n", - "0 1394.1750 0:23:14 17553.49 20057.43 17685.95 17685.99 94003.57 \n", - "0 1357.7237 0:22:37 18257.87 20041.38 18277.77 18277.80 91280.15 \n", - "0 1505.0091 0:25:05 16107.48 19187.17 16137.28 16137.32 93738.74 \n", - "0 1596.4828 0:26:36 14046.44 15868.38 14061.43 14061.46 91948.11 \n", + " s h:m:s max_rss max_vms max_uss max_pss io_in \\\n", + "0 6410.4036 1:46:50 10456.73 46762.75 10474.48 10474.75 54614.34 \n", + "0 10972.9724 3:02:52 10129.77 56932.70 10109.43 10110.02 84926.57 \n", + "0 6546.8879 1:49:06 10403.43 52091.42 10226.46 10227.06 59158.95 \n", + "0 8474.0678 2:21:14 10509.81 55628.16 10474.58 10475.17 74463.39 \n", + "0 6643.4003 1:50:43 10399.51 47443.64 10452.64 10453.31 57368.30 \n", "\n", " io_out mean_load cpu_time ident \n", - "0 1.14 2914.11 40626.79 a \n", - "0 1.16 2771.80 38643.81 b \n", - "0 1.01 2794.07 37936.37 c \n", - "0 1.02 2605.24 39209.39 d \n", - "0 0.96 2367.13 37791.57 e " + "0 73.48 586.18 37592.65 a \n", + "0 72.73 331.31 36359.01 b \n", + "0 73.10 530.59 34751.04 c \n", + "0 72.83 430.85 36527.69 d \n", + "0 76.80 530.69 35255.88 e " ] }, "execution_count": 8, @@ -996,43 +996,43 @@ " 0\n", " a\n", " mins\n", - " 23.235418\n", + " 106.840060\n", " \n", " \n", " 1\n", " b\n", " mins\n", - " 23.236250\n", + " 182.882873\n", " \n", " \n", " 2\n", " c\n", " mins\n", - " 22.628728\n", + " 109.114798\n", " \n", " \n", " 3\n", " d\n", " mins\n", - " 25.083485\n", + " 141.234463\n", " \n", " \n", " 4\n", " e\n", " mins\n", - " 26.608047\n", + " 110.723338\n", " \n", " \n", "\n", "" ], "text/plain": [ - " ident benchmark val\n", - "0 a mins 23.235418\n", - "1 b mins 23.236250\n", - "2 c mins 22.628728\n", - "3 d mins 25.083485\n", - "4 e mins 26.608047" + " ident benchmark val\n", + "0 a mins 106.840060\n", + "1 b mins 182.882873\n", + "2 c mins 109.114798\n", + "3 d mins 141.234463\n", + "4 e mins 110.723338" ] }, "execution_count": 9, @@ -1059,7 +1059,7 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -1096,7 +1096,7 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -1127,13 +1127,13 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 17, "id": "93be9183", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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2GT58uJRPcf78eZo1a8arV68ICAggKSmJX375RZq7/6GaNm3KkCFDpASuzDyGY8eOER0dzbBhw1QOwue2KlWqUL9+fc6ePUu/fv2wsbHh+fPnHD58mNTUVEqUKPFR37IBvvvuO/755x92797N7du3ad68OZGRkfzzzz+Ym5tLg749e/bk6NGjHDx4kNu3b/PVV1+Rnp6Ov78/L168YPz48Srn+WdlbGzM7t27uXv3LnXr1uXChQtcunSJJk2aMGjQIGm/SZMmcfHiRRYuXMiRI0eoX7++FJe2tjbz5s1Ta0bbx55vfuvatSsbNmzA0dGRDh06kJ6eTmBgIGFhYRgZGREXF8eLFy+y5ZaoY+rUqZw6dYrly5fz7bffYmZmhrOzM3PmzMHe3p6vv/4aPT09zp49y9WrV3FwcFCaAVbUiTuLQmDJkiVYW1uzc+dOzp8/T/fu3fHz81P61qOnp8emTZsYO3YsKSkpbN26lRMnTmBjY8OmTZukRLqP5eHhweLFi6lUqRL79u3D39+fqlWrsnLlSiZMmPCpp6gWLS0tVq9eTc+ePQkPD2fz5s2cO3cOW1tbdu7cSatWrXjw4AGPHj364GMXK1aMNWvW4OrqSnJyMj4+Ppw+fZquXbuydetW6du7TCZjxYoVTJ06lRIlSuDn54e/vz/Vq1fnt99+Y/jw4Wq1Z2pqire3N2lpaWzZsoVnz54xbNgw/ve//6GjoyPtZ2RkxI4dO/jhhx+IjIyUzrldu3bs2LFDmjKcV+eb39zc3Bg7dixaWlps3bqVw4cPU6lSJdavX8/IkSMBOHHixEcd28zMjNGjR5OYmIinpycAAwcOZNmyZZibm3PgwAF8fHxITU1l8uTJzJs3L9fO63MgU3zsQ14hz3l4eLBr1y52794tZVILgiBogrizEARBEHIkOgtBEAQhR6KzEARBEHIkxiwEQRCEHIk7C0EQBCFHorMQBEEQciQ6C0EQBCFHorMQBEEQciQ6C0EQBCFHorMQBEEQciQ6C0EQBCFHorMQBEEQciQ6C0EQBCFHorMQBEEQciQ6C0EQBCFHorMQBEEQciQ6C0EQBCFHorMQBEEQciQ6C0EQBCFHorMQBEEQcpTvnUVCQgL29vaEh4cDEBgYSLdu3bC3t8fd3Z3U1FQAoqKiGD58ON27d6dv377S/oIgCEL+y9fO4vLlyzg5OfHgwQNp29SpU1m2bBn79+8nOTmZPXv2AODu7k7btm3ZvXs3Dg4O/PLLL/kZqiAIBdSePXvo0qULXbp0YeHChQCEhoYycOBAunXrxtChQ3n58qWGo/z8aOdnYzt27GDGjBm4u7tL2+RyOQkJCcjlclJSUtDV1SUuLo5bt27h7e0NgKOjIy1atFCrjeTkZK5du4apqSnFihXLk/MoLORyOdHR0dStWxc9PT1Nh6NR4rr4T2G+LpKSkpg7dy4BAQEYGhri5OTEqVOnmDVrFlOnTsXW1pZffvmFdevWMXHixByPJ66L/+R0XeRrZzF37txs22bOnMnAgQMxMDDA3Nycjh07cvPmTSpWrMi8efMICQmhYsWK/Pzzz2q1ce3aNfr375/boRdqPj4+NGnSRNNhaJS4LrIrjNeFXC4nIyODpKQkSpYsSXp6Onp6epQsWRJbW1sARo4cyatXr9Q6nrgusnvXdZGvnUVCQgJ9+/YlPT0dgL///hsPDw/MzMxo0KABhoaGzJ8/H3t7e27cuIGDgwPbtm1j4MCBeHh4sHnz5hzbMDU1Bd6ccIUKFfL0fAq6iIgI+vfvL/1OijJxXfynMF8XBgYGuLi40KlTJ/T09GjWrBmRkZGYmJgwadIkbty4gZWVldpfLsV18Z+crot86ywuX77MtGnTePDgAUZGRgDMmjWLpk2bsmHDBpydnSlbtiz+/v4MGTIEfX19/P39SUtLw97enjlz5qjVTuatZIUKFTA3N8+z8ylMivrtNYjrQpXCeF3cunWLnTt3cuzYMUqVKsWECRMIDQ3lzJkzbNmyhXr16vHrr7+yYMECFixYkOPxxHWR3buui3wb4M4cryhXrpy0TSaTcevWLSIjI0lJSeHu3bvUq1ePL774Ai0tLZo1awbAsWPHqFOnTn6FKghCARUYGEiLFi0wNjamePHi9OzZk3Xr1mFhYUG9evUAsLe358qVKxqO9POTb53F3Llzsz0HmzNnDi9fvqRt27acPn2atLQ03N3dOXLkCE2bNuXixYsAbNq0iXnz5uVXqIIgFFC1atUiKCiIxMREFAoFR48eZeDAgdKkGICjR4+KL5d5IN/zLDIyMihRogRxcXH88ssvzJ49m2rVqqGnp8f9+/dJTk5mzZo1ODk5kZiYCICuri46Ojr5HepHCw0Nxc7ODh0dHezs7AgNDdV0SEIBIK6LT9e6dWu6dOlCz5496datG+np6Tg7O/Pbb78xbdo0unTpQkhICB4eHpoOVW2F5rpQ5KNLly4prK2tFdbW1ootW7Yoxo4dq7C1tVXcu3dPcefOHUWjRo0U7u7uivbt2yvq1Kmj+PbbbxVWVlYKW1tbxY8//qhWG48fP1ZYWVkpHj9+nMdn8262trYKQPpna2urkTgKwu+ioCgIvwtxXRQ8BeF3UViui3y9s9ixYwdlypTB2NiYKlWqcOXKFdLS0khISODQoUMYGBjQqlUrDhw4IM2lBli1ahXR0dH5GeonCQoKeu9roWgS14WgSmG5LvK1s5g7dy66uroAWFhY4OLigo6ODn369GHNmjWYmJjQsWNHihcvjoODg/Rzq1atokOHDvkZ6idp2bLle18LRZO4LnKHqgzuTMePH6ddu3YaiuzjFJbrIt/HLPbu3UtsbCwRERG0bt0agCpVqvDFF1+QlJQkTZF9+vQpTk5O6Ovrc+XKFQYMGJDfoX40b29vKleujJaWFra2tlImulC0ievi02VmcG/evJk9e/Zw7tw56Zt4TExMts6jMCgs10W+JuVl5lpkJuWdO3eO58+fs2HDBqpVq8YPP/zAsWPHAPj555959eoVrVu3plq1anh5eamVvl8QWFpaSlmh8+fP13A0QkEhrotPpyqDO/NpxbRp0/jpp59YsmSJhqP8MIXlusj3MYsZM2ZISR9WVlakpaURHh6OXC7n6dOnVK5cmbS0NIKDg2nYsCHLly+nd+/e0viFIAhF19sZ3La2tlSqVAkbGxs2bdqEtbU1DRo00HSIny2Nrg1VrVo1+vfvz4gRI9DS0sLAwIA//viDkJAQ5HI5ly5donv37igUCp48eZKfoQqCUACpyuBevXo1wcHBbNy4kYiICE2H+NnSSD0LmUwGvBm/8PX1pWrVqlSvXp3k5GT69u1LjRo1MDIyQk9PD4VCQfny5QtVnoUgCHlDVQb35cuXiY6OxtHRkeHDhxMVFUW/fv00HepnRyP1LDLHLHR0dGjbti3+/v6sX7+esmXLoq2tjZGRES9evOCnn35i7969lC9fXnouKQhC0aUqg7tevXocPHiQPXv2sG7dOsqVK8fWrVs1HepnR+NjFleuXCEmJoZFixZRo0YNGjdujI6ODgYGBgQGBgJvbj2rVq2an6EKglAAqcrgHj58uKbDKhI0Pmbh4uKCk5MTT58+xc7OTiqMNG/ePJydndm2bRs6Ojrs3bs3P0MVBKGAGj58+Ds7CHNzc44ePZrPERUNGh2zOHHiBBs3biQhIYGyZcty4cIFJk+eTHJyMosWLaJWrVpUr14dMzMzPD098ztUQRAE4f9pdMzCzs6OPXv2UKpUKX777TcMDAyYPHkyd+7cISIiAjc3N/bu3YudnR0hISH5GaogCAWUqgzuw4cP4+DgQLdu3Rg9erSowZ0HNDpmARAXF0dycjJbtmyhb9++VKlShcTERORyuVSMpHr16mLJYUEQVGZwHzlyhJkzZ7Ju3Tr27t1LzZo1WblypaZD/exovAZ3eHg4ZcuW5cyZM9L7cXFx1K5dmz59+pCcnIyhoSFeXl75GaogCAWQqgzuMmXKMHPmTMqXLw9AzZo12bdvn4Yj/fxofMzi559/JioqCrlcjq2tLSNGjCA9PZ179+6xYcMGVq5cSUpKCps2bcrvUAVBKGDelcGdudBocnIy69atK1QLjxYWBXLMwtTUFAsLC8zMzFi4cCElSpQQZRIFQVDK4A4MDERLS4v169cDEB8fz7Bhw6hVqxY9evTQcKSfnwI5ZtGoUSPi4uJwdXXlp59+Ijk5WYxZCIKgMoP7zJkzUtZ2rVq1VD7uFj5dvtezyFqH++0xi0GDBgGgp6dHly5dePjwIcuXLyclJaVQlUkUBCFvqMrgtra2ZuTIkXTq1ImpU6dKj7mF3JWvA9yQfcxi6dKlREVFUaxYMWxtbWnQoAHjx48nMDCQsmXLkpaWhkwmQ1s730MVBKGAad26NTdu3KBnz57o6OhQr149qlevztq1a5HL5Rw8eBCAunXrijuMXKbRehZ2dnbY2dnxzTffsHjxYsaPH8/kyZP5888/CQsLo2rVqshkMlJTU7G3t+fkyZP5Ga4g5KrQ0FB8fHx48uQJQUFBeHt7Y2lpqemwCh1VGdz29vYaiqboyNfOInPMIvNxE6gesxg6dCgNGzakQ4cOhIeH06tXL+rXr5+foQpFiJeXF6GhoXnejo+PD48fPwbg33//pU2bNlLRm7xiaWnJsGHD8rQNoWgokHkWZcuWlaa+paSkEB8fL6bCCXkmNDSUO3fvY1yhcp62E56lJkv4kyfExqfmWXuxEY/z7NialLm6LICtrS2TJk3i5s2bTJs2jYSEBJo0aYKnp6d4dJ3LCuSYxe+//87NmzeZPHkyYWFhVKpUia5du+Z3qEIRYlyhMl0Hj8/TNoKCgrh+8bT02rpBszxtc9/GwlVeVB2ZGdwBAQEYGhri5OREUFAQ8+bNY86cOTRs2JApU6awY8cOUdMilxXIPAsANzc3Xr9+Te/evbGxsWHHjh35Gaog5DqX6Uup0+hLihXTpk6jL3GZvlTTIRU6b2dwp6enk56ejra2NsnJyTRs2BCAnj17ijLMeaBAjlk8evSI8PBwRo8ezejRozl37hwrVqwQ3xSEQq2CuQXz1+3UdBiF2tsZ3Hp6ejRr1gwdHR1MTU2lfUxNTYmMjNRglJ+nAjlm4e/vT1paGgcPHuTgwYOkpqYSFRWVn6EKglAAqarBferUqWz7iVyL3KfRtaHgzW1lbGwsqampeHh4kJqaStOmTalVqxba2tooFApMTEwwNjbO71AFQShgVGVwh4SEEBMTI+0THR1NuXLlNBjl50mjYxYJCQmMHTsWbW1taUzizz//pHz58oSFheHs7MzevXsxNjYmLS0tP0MVBKEAUpXB3axZM3R1dTl//jwAu3fvxtbWVsORfn40OmZx6tQprK2tuXXrFpUrV2batGnI5XJMTU2RyWRcvXoVOzs7bt++LZKXBEFQmcE9fPhwvv76a6ZNm8br16+xtrZWGhcVcke+j1kkJCQgl8uJjo7m8ePHvHz5kpiYGOrVq4eZmRk7d74ZABwzZgxLlixh5cqVaGlpsWLFivwMVRCEAkpVBnetWrX4888/NRRR0aCRx1DwZsZCUlISly9fZs2aNVy6dAm5XM748eNJSkpixYoVTJkyhdu3b9O0aVNGjRqVn6EKBVR8fDzBwcH8/fffHDhwgLNnz5KQkKDpsIR84ufnh4ODg/SvcePGzJo1i8DAQLp164a9vT3u7u6kpuZdsmNRpdHHUM+fP8fExAQ7OzvgTW6Fn58fBw8epFixYnz//fcALFmyRGRwF2Hp6ekcOHCArVu3cvXqVYoVK4ahoSEKhUKqtdyoUSP69OlD586d0dLK93kbQj7p1asXvXr1AuDu3buMGTOGn376iR49erBhwwaqVauGs7Mze/bskfYTcodGp84aGBgQHx/P0KFDiYqKQqFQ0LZtW9LT05HL5YwePZrHjx+jr6+PtbV1foYqFBBBQUHMnTuXSpUq4eDgwKJFi6hcubI0o06hUHD//n3Onz+Pr68vK1euZPr06bRq1UrDkQt5bebMmbi5uWFkZIRcLpcecaekpKCrq6vp8D47GlnuI3PMQl9fHy0tLc6ePUtGRgba2tpkZGRQvHhxAO7du0d6ejr379+nffv2+R2qUADs3LmT1atXY2FhofJ9mUxG9erVqV69On369OHevXusWrVKdBafuaCgIJKTk+nUqRPwpuMYOHAgBgYGmJub07FjRw1H+PnR6JhFqVKlSE9PZ8eOHVy7do26dety/PhxTE1NsbS0ZOvWrejq6mJsbMz9+/fzM1ShgFiyZMk7OwpVqlevzq+//pp3AQkFwvbt2xkyZAjwJq/il19+Yf/+/QQGBtKgQQPmz5+v4Qg/Pxotq6qtrY1MJqN06dIAVK5cmVatWomyqsI7xcfH4+Pjw+zZs1mwYAF+fn4kJydrOiwhH6WmpnL27FnatWsHwLlz57CysuKLL75AS0uL3r17c+bMGQ1H+fnRaFnVV69e0bBhQ+zt7albty7nzp1j9OjRoqyqoFJwcDBt2rRh48aNREdHEx4ezpo1a/j666+5deuWpsMT8snt27epUqUKJUuWBMDKyoorV65IWdxHjhyhXr16mgzxs6TRJcrlcjm3bt3C3NyctLQ0UlJS2LhxI507dxZlVYVs5s2bR+/evXF3d1e6hmbPns20adPEPPsi4vHjx1SoUEF6Xa1aNVxcXBg0aBDFihXDwsKCWbNmaTDCz5NGy6qWKlWKpKQkFi5cSK1atRgwYACHDh0iPT1dlFUVsnn48CErVqxQWlusWLFiDBo0iB49emgwMiE/de7cmc6dOytt69Gjh7gG8liBHLMYOnQoK1as4O+//2bdunWUKVNGlFUVsLOzY//+/dm2Hzx4kObNm2sgIkEoOjSaZ/H2mEVKSgpmZmb4+flRpkwZUVZVAMDd3V36/3K5nN9++43jx49Tr149tLS0uHPnDhcvXixw3yojwh+yfNY4bl05R636TXCZvpQK5urP6hJU8/PzY8uWLdLr8PBwHBwc6Nq1K/Pnz+f169fUrFmTBQsWSFPwhdxRIMcsXF1dRVlVAUC6CwUoXbq01CmkpKQAb+5GK1eujFwu/+g2Gmm9pEHp5xgH/fpJsb6t24ptXL8fDsD1i6fxntCbFf064bzVn7NhT2latSIr+nWiikmZXGszK6vST7lM2Tw7viaoyuD+8ccf6d27N//73/+oVasW48aN488//xTF0nJZgRyzcHV1xc3NDblcTu/evUlISBA1dYuo/Jovn5aaQmzk41w73tmwJ9lej9q4m3OPowEIvh/OqI272TIw75JN01JT4DP+cp2ZwX316lUaNmxIrVq1AKTVq4XcpdG1oVSNWVhbW4uyqoKSjIwMjh49Kj2KnDlzpnRnAWBjY/NJ6wC9rNIIn9BQyPjkUCVmlcx5/Pix0usLT5Q7kAtPYtmYUSX3Gs1KGyyrfJ5L+7+dwb1u3TpKlizJmDFjePToEU2aNBFT7fNAgRyz8PX1FWVVBeBNEt6QIUN49OgRtWvXplKlSuzZs4eWLVtSsmRJoqOj8fT0pEGDBlhZWX1UG8OGDcvlqN8cc8iQIQQFBdGyZUu8vb0ZMmQI//77r7RP69atRabxR3o7g1sulxMYGIivry8VK1Zk6tSprFu3jrFjx2o4ys+L2p1FfHw8165dIy4uDplMhqmpKbVr18bAwOCDGsw6ZnHp0iWMjY0pVaoUz549Y+bMmQwaNIjq1aujUCjIyMigatWqZGTk4tc+odD47bffkMlkHD58GENDQ2m7h4cHlStXBmDgwIF4e3sXqA9eS0tLTpw4obQts8N4uwMpSh48eMDJkye5evUqsbGxaGlpYWJiQt26dbGzs8Pc3Fyt42RmcC9YsAAAExMTGjRoIF0PnTp1UhoEF3LHezuL3F4aOuuYhYmJCdra2vj6+lKuXDlOnDjBli1bpLKq+/bto1q1agwcOFAUYC+iDh06xOzZs5U6iqx+/PFHZsyYkY9RfRxVHUhRcPbsWX777TfOnz9PvXr1qF69OnXq1CEjI4Pnz5+za9cuFixYQLNmzRgxYgTNmjV77/GyZnC3bt2alStX8uzZM8zMzDh27JhYHigPvLOzyIulobOOWTRu3JjExEQmTpxIXFwcxYsXp3Xr1lSqVAl4s+ZLlSpVePz4MTY2Nrl53kIhERUVla2kbq9evZTuaGvUqEFcXFx+hyaoYcKECURGRuLk5MSqVave+STi9evXBAQEsGTJEszNzVmyZMk7j5k1g9vMzIxZs2YxcuRIUlJSqF27NpMmTcr1cynq3tlZ5MXS0FnHLHR0dGjQoAGxsbGkpaURExODqakp8GZ+/YwZM/D09KRUqVIifb+IKlu2LNHR0UofDlOmTFHaJyIiAhMTk/wOTVCDg4MDX331VY776evr4+joiKOjY453X6oyuNu0aUObNm0+JVQhB+98bpRXS0O/PWZRuXJlLC0tSU1NRU9PjxIlSrBnzx6io6P5448/qFmzJlWqVKFMmTIsWrRI7ViEz0ezZs3w8/N77z6+vr60bt06nyISPoQ6HUVWmZUzi4rQ0FB8fHxYtGgRdnZ2hIaGajokldQe4H716hV37twhPT0dhUKh9F6LFi3UOkbWMYvbt28THBzMjh07KFeuHP/88w9///03gYGBxMTEsGbNGmrVqsWwYcM4evSouLsogoYNG0bfvn2RyWQ4OztjbGwsvffq1StWrVrF0aNH+euvvzQYpaCuP//8k+3btxMaGoqOjg6WlpYMHTpU7RUa3pXBPX36dAB8fHwICAhg8+bNnxyrl5dXvnxw+/j4SNOs//33X9q0aUP//v3zrD1LS8uPmgGoVmexa9cuPD09VdYNkMlk3Lx5U63Gso5ZJCUlERERgYeHB1FRUaSkpODs7ExcXJw0UwKgdu3a6Ovrq3tOwmekZs2arFmzhqlTp+Ln5yfdacbHxxMWFka5cuVYu3atNBNGKLiWLl3K9u3bGTRoEGPGjCEjI4MrV67g7u6Os7MzgwcPzvEY76rBDW8qa/7+++8f9ETkfUJDQ7lz9z7GFfL22grPkn8T/uQJsfGpedJWbMTHJ56q1Vn8+uuv9O7dG2dn5w+eKvu2rGMWxsbGWFlZ8eTJE+RyOenp6SQlJUmDVN988w1paWmUK1cOHx+fj25XKNy+/PJLAgICOHXqFJcuXSIuLo7SpUvj4uKCra2tWAOokPDz82PhwoW0bdtW2ta+fXtq167NnDlz1Oos3vZ2De7U1FSmT5+Oi4sLu3fvzrWYjStUpuvg8bl2PFWCgoK4fvG09Nq6QbM8a3PfxndPHMiJWqvOvnr1ikGDBn1SR5Ep65hFnTp1UCgUUj1uPz8/5HI5jx49Ys+ePbi7u5OcnJzjc2vh86ajo0ObNm1wdXVl1qxZjB8/ng4dOoiOopAxMzPLts3CwoLU1A/7Jp21BveSJUtwdHRUO1ejIHGZvpQ6jb6kWDFt6jT6EpfpSzUdkkpqdRbt2rXjn3/++eTGMmtwZx2z2LJlC3v27MHDw4OKFStKSTYpKSl4eXlhZGTElStXPrl9ofDp168fQUFBau9/4sQJ+vbtm4cRCR8iIyND+jdq1ChmzJjBvXv3pPcfP37M3LlzGTly5Acd9+0M7lOnTvHs2TMcHR1zNfb8UsHcgvnrdrLr9EPmr9tZYFcnVusxlJGREcuWLePvv//miy++QEdHR+l9dWcqqTtm0aRJE1asWIGHhwcuLi78+uuvtG+fdwuuCQXX7NmzmTNnDp6enrRv355WrVpRrVo1ypYti1wu58WLF9y+fZtz587h7+9PpUqVmDNnjqbDFv6ftbW1UkKtQqGga9eu6OrqIpPJSE5ORiaTcf/+fX744Qe1jpk1g3v//v3cvXsXBwcHEhMTiYmJwdXVVa3ZmYL61OosEhISsLe3/+TG1B2zMDMzo169ety4cYOVK1eSnp7OiBEjPrl9ofCpVq0a3t7eXLhwge3btzNhwgRevHihtI+RkRGtW7dm8eLFNG7cWDOBCipt2rQp14+ZNYP77WVeQkJCWLVqlego8oBanUVurrmjaszi/Pnz6OvrEx8fj5+fH5UqVeLZs2cYGBiQlJSElpaWUl0DoeixsbGRsvifPHmitLbQ2wl7QsGS09IdHyNrBreQP97ZWSxfvpzhw4dTokQJli9f/s4DZM5/V4e6eRbbt2/nzp07WFpaoqWlxfPnz+ndu3euznIQCq9KlSpJS8IIBd/Vq1dZu3YtixYtQl9fHxsbG5KSkqT3mzRp8kF5EaoyuDM1b95clNjNI+/sLM6dO8eQIUMoUaIE586de+cBPmSBP3XHLGxsbHBycqJly5aEhIQwderUPPmGIghC3rpy5QoDBgygc+fOpKamoq+vj0KhYP78+ZQvX56IiAh+/vln9u3bJ6phFnDv7Cze7ulzIxsS1B+zePubY3x8PJGRkWKAWxAKodWrV+Pk5MTkyZOlbTKZjMaNG0uJlLdv32bnzp1qdRbvyuCuWbMmmzdvRiaTUbduXTw9PcW06lym9nIfx48fJzQ0NNt8aJlM9kGDz+qMWfTu3ZugoCBmzZpFeHg4DRs2FLeWglAIXbx4ETc3N6VtWZcLcnBwYOfOnWodT1UGd/fu3ZkwYQJ//fUX+vr6eHh4sHXr1g9O8hPeT63OYvLkyVJtCT09PaX3PqSzUHfMIjk5GXd3d7S0tHB1dSU4OJgTJ04UuQXGhHdLTU3l7t27GBkZqUz0EgqGlJQUSpUqpbRt06ZNSgPUBgYGH1UzOzOD29jYmJkzZ0pJw1ZWVjx9+vTTAheyUauzOHjwIL/++qvai329i7pjFiEhIbx8+ZI5c+bg4OCAiYkJAQEBorMoojZv3sy2bdtYt24d5ubmXL9+nVGjRhEVFYVMJqNz587Mnz9fPHYogMzNzbl58yYVK1aUttWrV09pn6tXr1KlSpUPOm7WDO7Mx9ZxcXH4+PgUqKqJnwu1MrjLly9P+fLlP7mxuXPn0qRJE+n122MWycnJpKWlkZSUxP79+0lPT2fDhg04ODiwatUqzpw588ntC4XPtm3bWLp0KR07dqRMmTIoFArGjx+PTCZj3759HDt2jGfPnrFmzRpNhyqo0LFjR5YvX05CQoLK9xMSEvjtt9/o1q3bBx337QzuTJGRkXz//fc4OjqKx9Z5QK3OwtPTE09PT3bv3k1ISAhnz55V+qeuzOS+zLnxlStXZu/evQwaNAgzMzOmTp3KiRMnqFu3LmXKlAHA0NAQZ2fnD/7mIXwefH19mTFjhrSI5fnz53nw4AFDhgyhRo0aVKhQgdGjR7N3715Nhyqo8OOPP6KtrU3Hjh1Zv349V65c4dGjR1y7do3Nmzfj4OBAmTJlGDhwoNrHzMzgbteunbTt/v37ODk50aNHD8aMGZMXp1LkqfUY6vr169y8eRMPD49s76m7RHnmeMWDBw8wMjIC3oxZnD59mvXr12NhYYFCoUBbW5vjx49TunRp9uzZw+bNm/Hx8clWWlMoGsLCwpTuRoOCgpDJZEpV0apWrUpUVJQGohNyoqenx9atW1m9ejXe3t4sXrwYmUyGQqGgTJkyODo64uzs/EFJt1kzuBMSEhg6dChubm44ODjk1akUeWp1FmvWrMHNzQ0nJ6dsA9zqyhyvcHd3lwa4U1NTWbx4MR4eHvj7++Pr60uPHj04fPgwV65c4eHDh7x+/ZqIiAgxs6GI0tPTIzExUXodFBSEubm50p3ms2fPKF26tAaiE9Shp6fHuHHjcHNz4/Hjx8TFxWFoaIiFhcVHrcyQNYP7zz//JCYmhg0bNrBhwwbgzeKnLi4uuXYOgpqdRfHixWnfvv0nFSDKzLHIyMggJiaGiIgIDh06RKdOnVi/fj1RUVGYmppib29P/fr1OXnyJN9++y0KhQIjIyPq1q370W0LhVfLli3x8fHB09OTCxcucPnyZYYPHy69r1AoWLdundLdh1Bw3LlzBysrK+DNU4gvvviCL7744r0/c/v2bWrWrPnO97NmcA8ePFh8mcwHao1ZjBs3joULF0p5Fm8vO5yRkaF2Y5cvXyY6OhqZTEZ4eDjPnj1j8eLFjB07FplMJiXpTJo0iUqVKjFjxgxWrFiBtrY2v/zyy8edoVCojRs3jpMnT9KkSRMGDhxI9erVpZKQ+/fvp1u3bly+fFntJWeE/DVnzhzGjx/PhQsXctz39OnTuLi4vHfVYD8/PxwcHKR/jRs3ZtasWQQFBdG1a1e++eYbli1blpunIPw/te4sli9fTmxsLCdOnFD5/oeUVS1TpgzFihXj2LFj3L17l27duvHgwQNkMhn37t0jLi6O+/fvo6WlJdVenjFjRraZD0LRULlyZfz9/Tl16hRaWlq0bNlSmiKblJRE8+bN+f7770VZ1QJq06ZN7Nmzh6lTpxIfH0/z5s2lJeYzMjJ4/vw5d+7c4cKFCxgYGDB8+HB69uz5zuOpSsobNmwYTk5ObN68GTMzM0aMGCHysvKAWp3F4sWLc6WxuXPn0q5dO9LT05k4cSLm5ubMnz+fr776isDAQAwNDSlbtizFihXD0NCQefPmcezYMZKSkjA1Nc2VGITCR1dXV2nmS6bMDw2hYMu8CwgODubff/8lODiYuLg4tLS0MDY2xtramn79+tG8efMPWmsuMynv8ePHWFhYSF8YunbtKvKy8sA7O4u4uDhp1pK6i/jFxsZibGz8zvcTEhKIjIyUpsVmVrgqX748Dx8+pF69eshkMlxdXZk+fTqvX78mJiaGUaNG4eHhkWtrVAmFS0REBPv27aNPnz4YGhqSmprK0qVLOXXqFEZGRgwdOhRbW1tNhynkoEWLFrRo0SJXjvV2Ut7+/fuVvkyWK1eOyMjIXGlH+M87xyx+/PFHli1bptYv/fHjxyxatOi9la4yS6rKZDJpBsT+/fu5fv06W7duJSMjg2vXruHq6kqLFi0wMDDA3NwchULB8OHDRVnVIurmzZvY29vj6+srJXZNmTKFzZs307p1a5o3b86ECRPe+YhU+Dy9nZSXda0p+LDVsAX1vPPOYvv27axfv55u3bpRuXJlWrVqhaWlpfSs8e1ylo8ePWLgwIHs2LHjnQ2pmjrr6enJ4MGDGT16NJs2bcLQ0FCqcKWlpUWzZs24ePEix44do06dOrl75kKhsHz5cr7++mvmzZuHTCbj6dOn/P333/Tq1YtJkyYBYGJiwpo1a8RjhyIia1nV8uXLExMTI70fFRVFuXLlNBXeZ+udnUXx4sUZNWoUQ4YMYf/+/fz777/s27ePuLg4ZDIZJiYmWFtb07dvXzp16iQlyLxL1uXJAZYsWYKjoyPm5uZK248cOULTpk25ePEi8GaQLPPCEIqWCxcusGXLFumbYuYdxNtlfhs3bizWAipCsiblNWjQgLCwMB4+fIi5uTn79+/H0dFRw1F+fnIc4NbT0+O7777ju+++y5UGMzIypIJKz549Y/LkyYSEhJCUlIShoSHR0dGsWbMGFxcX6S5DV1cXHR2dXGlfKFxSUlKUvogEBwdTsmRJqcRqJi0ttWaBC5+BrEl5urq6LFiwgLFjx5KSkoKdnR0dO3bUYISfJ7XrWeSGzDwLQJo66+DgwMuXL4mIiCA+Pp7jx4/z4sULRo0aJd1xPHjwgJkzZ+Ll5ZWf4QoFQI0aNbh06RLm5uYkJCQQGBiIra0t2tr/XboHDx6kRo0aGoxSUNf9+/e5du0a6enp2cYa1P1CqqqsaosWLcT6YHksXzuLt/MsMqfOpqam4ujoiJ6eHqampvTq1QsHBwf8/f2lClirVq3i559/zs9QhQJi6NChTJs2jUuXLnH58mVSU1P58ccfAaTxi7Vr1zJr1iwNRyrkZN26dSxdupTSpUtnWw1CJpPl2tMLIW/ka2fxdp5FpiVLlmBra0tgYKC0rXjx4koLgq1ateqTa2nkp9DQUHx8fHjy5AlBQUF4e3uLhRA/UqdOnShRogR//fUXZmZmTJgwQVr6ZcOGDezduxc3Nze6d++u2UCFHHl7ezNx4kSGDh36Scc5evQoq1atIjExkdatWzNt2jQCAwNZtGgRGRkZWFtbM2fOHFHfJJfla2cBsHfvXpo3b05ERAQPHz7k2bNnrFixgtTUVHbt2iXt9/TpU8aPH4++vj5Xrlxh4cKFn9y2l5cXoaGhn3ycnPj4+PD48WMA/v33X9q0aUP//v3ztE1LS0tpGYzPTZs2bZRWmc00btw4pkyZIsYrCom0tDS++eabTzrG48ePmTFjBn5+fhgbG/P9999z4sQJpk+fzoYNG6hWrRrOzs7s2bNHJG3mMrU7i5iYGPz8/Hjw4AHu7u6EhIRgaWlJrVq11G4sa1nV/fv3c/fuXTp27MijR49QKBS4urry66+/8vPPP/Pq1Stat25NtWrV8PLyYuLEiR9+hm8JDQ3lzt37GFfI26Uhwp88yfY6Nj71HXt/utiIx3l27ILi9u3baGtrY2lpKc2Myhz4vnXrFp6enmzbtk2TIQo5cHBwwMfHh0mTJn10HsShQ4fo3LmzNMC9bNkydHV1kcvlJCQkIJfLSUlJQVdXNzdDF1Czs7h69SqDBw+mTp06XLhwgZ9++okzZ87g4eHB6tWrad26tVqNZS2rOn/+fFJTUxk8eDDt27fH19eXX3/9lbS0NIKDg+nRowdz5swhIiKCAQMGfHJnAWBcoTJdB4//5OO8T1BQENcvnpZeWzdolqdt7tu4JM+OrWl3797lp59+4tGjR8CbAe/ff/8dMzMzEhISWLJkCb6+vmJtqELg+fPn/PPPP+zbt49KlSplm+Ho4+OT4zEePnyIjo4OQ4cOJTo6mrZt2+Lq6srMmTMZOHCglMwrZkPlPrU6iwULFjB8+HBGjBhBo0aNgDfrspiYmLBkyRK1O4v35VrEx8dL20JCQpDL5Vy6dInu3bujUCh4kuXbekHmMn0py2eN49aVc9Sq3wSX6Us1HVKhNWfOHAwMDPDx8UFHR4cVK1YwZ84cnJ2dGTFiBC9fvsTFxUUsNFkIWFpaMnLkyE86hlwu59y5c2zevJmSJUsyevRovLy8+Ouvv9i/f7+03tz8+fOZMWNGLkUugJqdxY0bN1QmPTk4OHzwdNaEhATpFvTUqVOEhIQQGBhIYmIi+vr6KBQKatSogZGREXp6eqSlpVG+fHnCwsI+qB1NqmBuwfx1OzUdxmfh2rVr/O9//5O+pMybN48OHTpw69YtatSowaxZszAzM9NwlII6fvrpp08+homJCS1atJDWrWvfvj1btmzByspKqpPRu3dvXF1dP7ktQZlanYWxsTH379/PVrTk/PnzH5RWn3XMwtfXl7t372JpaUmxYsWIiIhg4MCBeHt78+LFC+bNm0fbtm2ZNm2aeAZZRL1+/VrpEVPmgnGtW7fG09NTU2EJanJ3d2f69OkYGBjg7u7+3n0XLVqU4/Hatm3LpEmTePXqFfr6+pw8eZIBAwbg5eVFTEwMJiYmHDlyhHr16uXWKQj/T63OYtiwYfz8888MGzYMhUIhrRa7adMmJkyYoHZjWccsVqxYQVpaGjo6Ohw+fJgJEybg7u6Ojo4OBgYGBAYG0rZtW27dukXVqlU/7gyFQi/rYKiWlpZ0DQkF29tlUz+mhGpWDRo04Mcff6Rfv36kpaXRqlUrnJycKFmyJIMGDaJYsWJYWFiIvJs8oFZn0adPH0xNTVm/fj16enosWbKEqlWrMnfu3GyZlO+jasxCR0eHHTt2MHfuXIoXLy7Nrpo3bx7Ozs5s27YNHR0dkZ0pKBFz6AuHtx9f59b6XaqWH+rRowc9evTIleMLqqk9dbZdu3YqC9B8qLfHLAC2bt2Kj48PFStWRCaTsXLlSsaMGcOiRYuoVasWcrmc1NRUPD09pWLsQtHi5eVFiRIlpNdpaWls3LgRQ0NDpf1cXFzyOzRBKDLU6iySk5PZuXOnVIM7q9mzZ6vVWNYxi/Pnz7N27VoCAgLQ1dXF3t6e06dP8/XXXxMREcFvv/2Gra0t8+fPZ8uWLR9wWsLnomnTply/fl1pW6NGjbhz547SNlG/oOhQlcF98eJF5s+fz+vXr6lZsyYLFiwQd5+5TK3Ows3NjbNnz9KsWTP09PQ+urGsYxalSpWiWLFipKenk5ycTHR0NF9++SWJiYnI5XJpIcHq1auLehZFlKiOKLxNVQb34cOHmTlzJv/73/+oVasW48aN488//6Rfv36aDvezolZncfr0aby8vGjSpMknNZZ1zMLKyooRI0bQuXNnYmNjKVeunFT1rHbt2vTp04fk5GQMDQ3FirOCIKjM4L506RINGzaUxjunTZuGXC7XZJifJbU6i6pVq+baLz/rmEVGRgalS5emVKlSyGQy1q5dS40aNbh37x5btmwhNjaWCRMmiAJIglCInTp1Cl9fXy5fvszz588pU6YMDRo0oE+fPmon9YLqDG59fX1KlizJmDFjePToEU2aNMHDwyMPz6ZoUjuD28XFhS5dulCxYsVsC7epu+KnumMWLVu2xMLCAjMzM9zd3SlRooSowS0IhdTs2bPZtm0bX331Ff3796d06dJERUVx9epVfvzxRwYMGMC0adPUOpaqDO6mTZsSGBiIr68vFStWZOrUqaxbt46xY8fm8ZkVLWp1Frt27SIsLIzNmzdnG7OQyWRqdxbqjlk0atSIuLg4XF1d+emnn5g5cyZffvnlh52ZUKRkZGSI1WcLoN27d7N//362bdtGgwYNsr1/8eJFRo8eTf369enWrVuOx1OVwb1w4UJatWolJW926tRJTIjJA2r917V9+3YWL15MSEgIJ06cUPp3/PhxtRubO3eu0rjH22MWrVq1Ql9fnwkTJqCnp0eXLl14+PAhy5cvJyUlRdxWCkyZMoWEhIRs269du0bPnj01EJGQk61btzJ+/HiVHQW8mdk2btw4tRYRhDcZ3IGBgbx69Qq5XM7JkycZPnw4169f59mzZ8CbKpxiQkzuU6uzKFu2LDVr1syVBt81ZlGlShX09fVZu3Ytd+7cITAwkLJly1KsWDFkMplSGU2haLp27RpdunTh33//Bd5M6Z4/fz59+vQRxaUKqLt379KiRYv37tOyZUvu3r2r1vHezuDu3LkzFStWZPTo0cyaNYuRI0fSsWNHXr58yYgRI3IjfOEtan0CT5s2jRkzZjB69GjMzc2zfXCruzy0umMWCoWCsLAwqlatikwmIzU1FXt7e06ePPmBpyd8Tv766y+8vLwYO3Ys7dq14+rVqxQvXhwvLy9atmyp6fAEFYoXL87r16/fu098fLxUm0QdqjK431UgS8g9anUWo0ePBpAqsWXeGSgUCmQyGTdv3lSrMXXHLIYOHUrDhg3p0KED4eHh9OrVi/r163/wyQmfF21tbQYOHMjNmzfx9/dHW1ubOXPmiI6iAGvSpAk7duxg+vTp79zHz8+Ppk2b5mNUwsdQq7M4cuRIrjSmbp6Fvr6+VHM7JSWF+Pj4QlWDW8gbO3fuZOnSpRgZGeHj48OtW7eYPXs2u3fvZvr06eJRVAE0ZswYnJycKFWqFMOGDcPAwEB678WLF6xcuZJdu3axY8cOtY+pKoM7k4+PDwEBASKZMw+8s7N4e3ZJbtYLUCfPYvz48dy8eZPJkycTFhZGpUqV6Nq1a67FIBROM2fOZMSIEYwYMQIdHR0aN25Mhw4d8PT0xMHBgatXr2o6RCELa2tr1qxZw6RJk1i/fj1Vq1bF0NCQmJgYnjx5QoUKFfj999+pXr26Wsd7Vw1uOzs77t27x++//46FhUUen1XR9M7Ook6dOgQGBmJsbIy1tfV7195R9zGUumMW8GaJEblcTu/evUlISGDHjh0ifb+I2717N9WqVVPaVr58eVavXs0///yjoaiEnLRs2ZIjR45w9OhRrl27xsuXL2nUqBENGzbE1tb2g9ZwelcN7tTUVKZPn46Liwu7d+/OozMp2t7ZWfzxxx+ULl0agE2bNuVKY+qOWTx69Ijw8HBGjx7N6NGjOXfuHCtWrBCdRRFXrVo1oqOjCQsLU1pRIDU1lfv372swMiEnxYsXp2PHjp9cG/tdNbgXLFiAo6OjtJ6ckPve2Vk0a9ZM+v+7du1i6tSpSs8bAV6+fMnPP/+stO/7zJ07l4SEBORyOdHR0TRp0oTGjRvz5ZdfIpfLKVGiBC4uLvj6+pKWlsbvv//O2rVrpemzQtG2bds25s6dS3p6OjKZDIVCAbyZcNGgQQNGjRql4QiFrJYvX672vuosMa8qg9vPz49nz54xefJkQkJCPiVc4T3e2VmcO3eOBw8eAG9u/2vVqoW+vr7SPqGhoZw6dUrtxjIfQ8Gb8phhYWFcuXKFM2fOoKurS8eOHXF1dcXZ2Rl9fX2WLVuGnZ0dU6ZMybVBdqHw8vLyYuTIkQwfPpx27drh5+fH69evcXd3p3379poOT1Dh3Llzau2n7pdBVRncFy9e5O7duzg4OJCYmEhMTAyurq78+uuvHxu2oMI7OwsDAwPWrFmDQqFAoVDg7e2ttJyCTCajZMmSOdbVfVvWx1AvXrygf//+0h1L8+bNCQkJoXz58qSlpUnzs58/f57trkYoeqKioujevTvFixenTp06XLx4kc6dOzNlyhSmTJkiTe0WCo7cnpWkqgZ3+/btpSp8ISEhrFq1SnQUeeCdnUWtWrWkb/MDBw5k1apV0hjGx8o6dVZfX58//viDHj16kJaWhr+/P126dKFSpUqUK1cODw8P5s2bR2JiIkOGDPmktoXCz9jYmLi4OMzNzbG0tOTmzZt07tyZ8uXLExUVpenwhHygqga3o6OjpsMqEtTKs8jNbwdZxyxsbGxo2bIl6enplClThsmTJ5OcnCw9l3758iU6OjqcP38+12IQCqfOnTszadIk5syZw1dffcWECROoXbs2x44dE9MlixBVGdyZmjdvTvPmzfM5oqIhXxdcUjVmcf78eUxMTBg4cCB37tzBz88PGxsb4uLiRFlVQcn48eMxNDTkxYsXtG/fnl69ejFr1izKlCnDvHnzNB2eIHzW8nVN58wxi2LFigFIU2bd3NwYOnQoVlZWPH36VJRVFVTS1tZm1KhR0mC2m5sbp0+fJiAgABsbGw1HJ+SXo0eP0rNnTzp27MicOXMA8PX1xd7enq5duzJ58mRSU1M1HOXnJ1/vLLKOWZw6dYr4+Hg2bNiAl5cXDx48oHPnzsTFxYmyqkI2ycnJ7Ny5k9DQUJUfBrNnz9ZAVEJ+UpXB/ccff+Dj48Nff/2Fvr4+Hh4ebN26lcGDB2s63M9Kvq/7/fZyH4MHD6ZEiRJ4e3vz5MkTqlevzpw5cwgICBBlVYVs3NzcOHv2LM2aNctWhEsoGlRlcKenp1OjRg1pxmTmEwohd2lkzCJzuY+wsDDWrl2LQqHA1dWVO3fusHXrVmrWrCnKqgrZnD59Gi8vL6UCWkLR8q4M7kqVKgEQFxeHj4+PNJVWyD0Fcswia1nV5ORkMWYhULVqVaVlPoSiRy6XExwczOLFi9mxYwdXr15l165dAERGRvL999/j6OgoZkTlgQI5ZpFZVvXAgQOirKogWbBgAS4uLnTp0oWKFStmq7mtbi14ofBSlcF95coVGjRowLBhwxgwYAA//PCDhqP8PBXIMYu3y6qmpaWJsqoC8GaNsrCwMDZv3pxtzEImk4nOoghQlcHdokULhg4dipubGw4ODpoO8bNVIMcsYmJiRFlVIZvt27ezePFiUdukCFOVwS2Xy4mJiWHDhg1s2LABgHbt2qm1MKGgvnztLLKuDZU5ZuHh4YGDgwPr16/n6dOnjBo1SpRVFbIpW7YsNWvW1HQYgoapyuAWj57yXoEcsyhbtqwoqypkM23aNGbMmMHo0aMxNzfP9miycuXKGopMyE+qyqoGBQUxf/58UlJS6NSpE25ubpoO87NTIMcsAFFWVchm9OjRANLqspnXkUKhQCaTqV2xUSi83lVWdcaMGWzevBkzMzNGjBghlVoVck+BHLMYPHiwKKsqZCNqmgiqkvIePnyIhYWFdGfZtWtXAgICRGeRywrkmIUoqyqokpl4JRRdqpLyatSogampqbRPuXLliIyM1GCUn6cCOWbh7+9PWloaBw8e5ODBg6Smpop6BYIgqCyrWqJEiWz7iTLMuS9fM7gh+5jFtWvXsLCwID4+nlGjRrFo0SKqVKkirfNiaGiIp6en0jcHQRCKpreT8vT09Gjfvj2nTp0iJiZG2icqKopy5cppMMrPU752FpcvX8bJyUkas4iMjGTgwIEcPHgQGxsbxowZA8DevXvR0dFhz549fPPNN6xZs0b88QVBoG3btgQGBvLq1SvkcjknT56kY8eOhIWF8fDhQ+RyOfv378fW1lbToaotIvwhk4c70uNLCyYPdyQi/KGmQ1JJo2MWO3fu5Pbt2zRu3JivvvpK2k9PTw8tLS3Onz9PUlISz549e2dlLEEQig5VSXlOTk5YWloyduxYUlJSsLOzo2PHjp/cViOtlzQo/RzjoF8/PfD36LZiG9fvhwNw/eJpvCf0Zq+zU560ZVX6KZcp+1E/q9Exi5IlS5KYmMi9e/dYsWIFf/zxh5R5efLkSQYNGkRGRgZ2dnZSByMIQtGmKimvRYsW7N27V0MRfZqzYU/f+7qg0MiCS+XKlWPq1KmsX7+ewYMH4+HhwYMHD+jduzc9e/bEycmJSZMmcfDgQe7du0dwcDCRkZEi6UoQhHxzMaM0h+NL0LWHa562U7PBSa5fPP3W62YEt8ybNvdtXIJxqeL0/oifzfcB7suXLxMdHU14+JvbrsjISIKDg7l69SrwZj360NBQ9u3bR9u2bTl69ChaWlqixrIgCAAMGjSILl264ODggIODA5cvX2bPnj106dKFLl26sHDhQk2H+EFcpi+lTqMvKVZMmzqNvsRl+lJNh6RSvt9Z7NixgzJlykg1Lfbt24eZmRkVK1YE3qz/o6Ojw7Vr1/D29ub8+fOULVuWSZMm5XeogiAUMAqFgtDQUI4fPy4t95KUlMSwYcMICAjA0NAQJycngoKCaNmypYajVU8Fcwvmr9up6TBylO93FnPnzkVXV1d6/eOPP1KlShXptUwmw83NjfT0dL788kt++OEHzMzM0NHRye9QBUEoYEJDQ5HJZAwbNoxu3bqxZcsW5HI5GRkZJCUlkZ6eTnp6utJnjJA7NJJnUbJkSaVtCoVC6XWVKlVITk5m9OjRyOVyunfvLoofCYLAq1evaNGiBb/99hsbN25k+/btXL58GRcXFzp16oStrS2VKlXCxsZG06F+djSSZ/HgwQMAYmJiGDlyJAEBAUr7mZqaoq+vL2Vy29vbixrcgiDQqFEjFi1aRMmSJTEyMuK7775j69at7Ny5k2PHjhEYGIiWlhbr16/XdKifHY3U4M5MsDty5Ajt27enU6dOSvt98cUXaGlp0axZMwCOHTsmanALgsC5c+cIDg6WXisUCg4fPkyLFi0wNjamePHi9OzZkzNnzmgwyg8jkvJUyJpn0adPH8zNzTl//rzS9iNHjtC0aVMuXrwIwKZNm1iwYEG+xSkIQsEUHx/PihUr2L59O2lpaezatYuxY8dy6NAhEhMTKVGiBEePHqVevXq50l5sxGP2bVySK8d6l327fIl4+gR4k5Q3fUwvuvbokydtxUY8xrhUtY/6WY3kWWRkZGRb/Ctz3CI6Opo1a9bg4uLCr7/+CoCurq4Y4BYEgbZt23L58mW6d+9ORkYG/fr14/vvv5fuKHR0dKhXrx7Dhw//5LYsLS1zIeKcRUU8y/bauFTxPGnLuFS1jz6vfO8sMvMsMmXmWcTExNC7d2+OHz/OixcvGDVqFObm5gA8ePCAmTNn4uXlld/hCoJQwLi6uuLq6qq0bfjw4bnSQbwts8hWXgsKCuLff/+VXrdu3Zr58+fnS9sfIt9nQ2XmWRgbGwP/5Vlk1tju1asXBw4cYO7cudLA96pVq5Q6GEEQhM+Ft7c3lStXRktLC1tbW7y9vTUdkkr5fmcxd+5c2rVrJ608++OPP3Lv3j0ePvxvUKd48eI4ODhIr1etWiVqcAuCALzJ4I6NjZWS8mbNmkVsbGy2utyFhaWlJf379wcokHcUmfL9zgLeLEEeGxtLREQEAAsWLCA6OlppoPvp06c4OTmhr6/PlStXGDBggCZC/WiFZYaDIBQmmRnce/bskf4ZGRkxY8YMVq9ezb59+7hx4wYnTpzQdKifHY2MWbxdhzsyMpIZM2bw5MkTpf1+/vlnXr16RevWralWrRpeXl5MnDjxk9rOryWHofAsOywIhcnbGdyxsbH07t2b1NTUbHW5RQZ37tPImMWMGTOU1oZq3769NJgNkJaWRnBwMA0bNmT58uX07t07W+JeQVdYlh0WhMJEVQa3n58fcrmcoUOH0q1bN7Zu3Urp0qU1HepnJ9/vLCZPnkzfvn2lqbLW1tbMnz+fp0+fSivPhoSEIJfL2bdvH/v27UNbW5vExMRPbjsvlxyOCH/I8lnjuHXlHLXqN6FqrfrcvXFJer+gLjssCIVJo0aNaNSoEfCmHs53333H7du3CQ4OVqrLvWvXLnr27KnhaD8v+dpZZD6CevDgAaamppQtW5ahQ4eyefNmVq5cKT1rrFWrFjo6OqxcuRI7OzvmzZvHli1bciWGvEqyyZpYY2xsQrnyFYiOjqJ8BTPq1rHOs+SeT0m0EYTC5Ny5c6SlpdGiRQvgzRhGmTJlpLrcAO3bt+fKlSuis8hlGimr6u7uTnp6Ordu3cLCwkKaNtawYUMCAgJo2bIlcrmc+Ph44E2NC319/U9uPy+TbLIm1sTFxdKrV698Sez5lEQbIX/FxcWxaNEiJk2aRNmyYpzpQ6nK4J42bRrTp0/n1atX6Ovrc/LkSdq3b6/pUD87Gl3uIzY2FlNTU+m1oaEht27dQkdHhwYNGjB58mQWLFhAamoqX3/99Se3n5dJNlkTa8zNzbG0tCzQU+GE/Ld9+3Zu3LjB9u3bGTVqlKbDKXRUZXA3a9YsW11uR0dHTYf62cn3MYuEhAQiIyMpU6YMCoWC6OhounbtypMnT6hevTqlSpUiOTmZyMhItLW1efnyJcWKFZMq6xVU3t7eDBkyhKCgIGxsbHj8+DGLFi0iKCgIb29v8c1f4MKFC8yYMYPY2FiCg4P58ssvpefvgvpUZXCrqstdWISGhuLj48OTJ08K9OeFRpYoT09PZ/ny5VSrVo0LFy6wevVqzpw5Q1JSEhkZGdy5c4eYmBiWL1/O1atX6dOnT7bFBgsaS0tLTpw4QVpaGnp6ejx79oyMjAz+/fdfhgwZounwhAKgT58+xMTEoFAopOVtBGHIkCE8fvy4wH9eaGSJ8sxps5kyMjKQyWQApKenk5iYiFwul6bTVq9evVAtUR4UFPTe10LRdP/+/fe+FtSjqgZ3poULFxa6QmmF5fNCo2MWL168wMbGhrFjx5KSkoKVlRUJCQnExcVRu3Zt+vTpQ3JyMoaGhoVqEcGWLVsqjV8UllrAQt6qVq0a9+7dU3otfBhVNbgzBQcHs2vXLtq0aaOZ4D5SYfm80EhZ1cy7iMxcC4VCgUKhoHjx4mhpaZGens69e/fYsGEDK1euJCUlhU2bNuV3qB/N29sbW1tbtLW1C/TCYEL+8vX1xcTEBJlMhomJCTt27NB0SIWOqhrc8OaL57Jlyxg5cqSGI/xwheXzQiN5FplLfZQtW5YLFy5w4MABzMzM6NGjByYmJpiammJhYYGZmRnu7u6UKFGiUJVVzRy/EIS32djY4OnpSUBAAJ06dRKD2x8hM4N75syZJCcnM2jQIKpWrYqvry9ubm48e/Ys54MUMIXl86JAjlk0atSIuLg4XF1d+emnn0hOTi5UYxaC8C59+/bF2tqavn37ajqUQklVDW5XV1fMzMykRD0hbxTIMQs9PT26dOnCgQMHWL58OSkpKYVu0EoQVDEyMhIlgj+BqgzuunXrcurUKRwcHHj58iWJiYnMmzePKVOmaDjaz4tGyqpWqFCBChUq8OzZM0xNTfnjjz+AN7MA1q9fz507d7h+/TrHjh0jIiKCQYMGScWSBEEoulRlcHt6ekqP9P766y/OnDkjOoo8oJHOIlP58uWJiYmRXkdFRVGuXDkCAgKIjo7G0dGRtLQ0oqKi6NevH1u3bs3xmHK5HECqlVGUZf4OMn8nRZm4Lv5TmK8LVRncnzL2I66L/+R0XWi0s2jQoAFhYWE8fPgQc3Nz9u/fj6OjI506dcLZ2RmA8PBwBg0apFZHAUjlVzMrTwlvficWFhaaDkOjxHWRXWG9LlRlcGfq2bPnBy0gKK6L7N51XWi0s9DV1WXBggXSmIWdnR0dO3b8pGPWrVsXHx8fTE1Nsw2kFzVyuZzo6Gjq1q2r6VA0TlwX/xHXxX/EdfGfnK4LmSIz2UEQBEEQ3kEjNbgFQRCEwkV0FoIgCEKORGchCIIg5Eh0FoIgCEKORGchCIIg5Eh0FoIgCEKORGchCIIg5Eh0FoIgCEKO/g8mLSCsc+52iAAAAABJRU5ErkJggg==\n", "text/plain": [ "
" ] @@ -1161,7 +1161,7 @@ "\n", " #axes[n].set_xlabel(xlabels[n], size=14)\n", " axes[n].set_ylabel(xlabels[n], size=14)\n", - " axes[n].set_ylim(ylim[n])\n", + "# axes[n].set_ylim(ylim[n])\n", "plt.subplots_adjust(wspace=1)" ] }, @@ -1228,58 +1228,58 @@ " \n", " \n", " 0\n", - " 814.4291\n", - " 0:13:34\n", - " 2246.58\n", - " 2380.33\n", - " 2243.58\n", - " 2244.08\n", - " 89.14\n", - " 0.11\n", - " 341.55\n", - " 2782.05\n", + " 635.5993\n", + " 0:10:35\n", + " 2276.08\n", + " 10742.91\n", + " 2258.54\n", + " 2263.37\n", + " 0.00\n", + " 7.33\n", + " 376.03\n", + " 2394.75\n", " 4\n", " \n", " \n", " 0\n", - " 484.0369\n", - " 0:08:04\n", - " 2661.74\n", - " 3352.14\n", - " 2661.75\n", - " 2662.25\n", - " 1189.09\n", - " 0.11\n", - " 649.08\n", - " 3142.19\n", + " 366.8955\n", + " 0:06:06\n", + " 3893.58\n", + " 13670.58\n", + " 3891.74\n", + " 3894.74\n", + " 106.28\n", + " 7.14\n", + " 658.99\n", + " 2422.29\n", " 8\n", " \n", " \n", " 0\n", - " 329.2121\n", - " 0:05:29\n", - " 6144.40\n", - " 7038.87\n", - " 6169.71\n", - " 6170.21\n", - " 7404.52\n", - " 0.10\n", - " 1137.80\n", - " 3746.52\n", + " 241.8623\n", + " 0:04:01\n", + " 4217.00\n", + " 13616.37\n", + " 4178.51\n", + " 4181.75\n", + " 0.00\n", + " 7.04\n", + " 1126.57\n", + " 2729.88\n", " 16\n", " \n", " \n", " 0\n", - " 154.1568\n", - " 0:02:34\n", - " 8026.29\n", - " 8707.47\n", - " 8042.18\n", - " 8042.25\n", - " 0.07\n", - " 0.11\n", - " 2112.52\n", - " 3256.75\n", + " 190.5965\n", + " 0:03:10\n", + " 7835.11\n", + " 13411.27\n", + " 7682.85\n", + " 7684.71\n", + " 23.64\n", + " 6.94\n", + " 1537.50\n", + " 2934.33\n", " 32\n", " \n", " \n", @@ -1287,17 +1287,17 @@ "" ], "text/plain": [ - " s h:m:s max_rss max_vms max_uss max_pss io_in io_out \\\n", - "0 814.4291 0:13:34 2246.58 2380.33 2243.58 2244.08 89.14 0.11 \n", - "0 484.0369 0:08:04 2661.74 3352.14 2661.75 2662.25 1189.09 0.11 \n", - "0 329.2121 0:05:29 6144.40 7038.87 6169.71 6170.21 7404.52 0.10 \n", - "0 154.1568 0:02:34 8026.29 8707.47 8042.18 8042.25 0.07 0.11 \n", + " s h:m:s max_rss max_vms max_uss max_pss io_in io_out \\\n", + "0 635.5993 0:10:35 2276.08 10742.91 2258.54 2263.37 0.00 7.33 \n", + "0 366.8955 0:06:06 3893.58 13670.58 3891.74 3894.74 106.28 7.14 \n", + "0 241.8623 0:04:01 4217.00 13616.37 4178.51 4181.75 0.00 7.04 \n", + "0 190.5965 0:03:10 7835.11 13411.27 7682.85 7684.71 23.64 6.94 \n", "\n", " mean_load cpu_time threads \n", - "0 341.55 2782.05 4 \n", - "0 649.08 3142.19 8 \n", - "0 1137.80 3746.52 16 \n", - "0 2112.52 3256.75 32 " + "0 376.03 2394.75 4 \n", + "0 658.99 2422.29 8 \n", + "0 1126.57 2729.88 16 \n", + "0 1537.50 2934.33 32 " ] }, "execution_count": 14, @@ -1323,13 +1323,13 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 16, "id": "5510d1fe", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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" ] From df8bef1bae8986b3a3ebeab6052b90231484473e Mon Sep 17 00:00:00 2001 From: "C. Titus Brown" Date: Mon, 28 Aug 2023 05:30:42 -0700 Subject: [PATCH 09/27] implement -c --- benchmarking.snakefile | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/benchmarking.snakefile b/benchmarking.snakefile index 5bae984..3f17b3c 100644 --- a/benchmarking.snakefile +++ b/benchmarking.snakefile @@ -22,15 +22,15 @@ rule a_vs_a: against="data/wort-list-a.txt", output: csv="outputs/output_a_vs_a.csv", - resources: - only_one_job=1, +# resources: +# only_one_job=1, benchmark: "benchmarks/a_vs_a.txt" threads: 32 shell: """ - export RAYON_NUM_THREADS={threads} + #export RAYON_NUM_THREADS={threads} {manysearch_cmd} -k 31 --scaled=1000 -o {output.csv} \ - {input.queries} {input.against} + {input.queries} {input.against} -c {threads} """ rule a_sub_vs_a: From 0f64aed78231de3293c93ca23a97eb01e108bc0d Mon Sep 17 00:00:00 2001 From: "C. Titus Brown" Date: Mon, 28 Aug 2023 08:01:20 -0700 Subject: [PATCH 10/27] update for new pyo3_branchwater --- README.md | 2 +- benchmarking.snakefile | 32 +++++++++++--------------------- environment.yml | 2 +- 3 files changed, 13 insertions(+), 23 deletions(-) diff --git a/README.md b/README.md index 025a6a5..12702ed 100644 --- a/README.md +++ b/README.md @@ -15,7 +15,7 @@ srun -p high2 --time=72:00:00 --nodes=1 --cpus-per-task 64 --mem 80GB --pty bash then run the snakemake workflow: ``` -snakemake -j 64 -s benchmarking.snakefile --resources only_one_job=1 +snakemake -c 64 -p -s benchmarking.snakefile --resources only_one_job=1 ``` ## appendix diff --git a/benchmarking.snakefile b/benchmarking.snakefile index 3f17b3c..e89afae 100644 --- a/benchmarking.snakefile +++ b/benchmarking.snakefile @@ -22,13 +22,12 @@ rule a_vs_a: against="data/wort-list-a.txt", output: csv="outputs/output_a_vs_a.csv", -# resources: -# only_one_job=1, + resources: + only_one_job=1, benchmark: "benchmarks/a_vs_a.txt" threads: 32 shell: """ - #export RAYON_NUM_THREADS={threads} {manysearch_cmd} -k 31 --scaled=1000 -o {output.csv} \ {input.queries} {input.against} -c {threads} """ @@ -45,9 +44,8 @@ rule a_sub_vs_a: "benchmarks/a_{n}_vs_a.txt" threads: 32 shell: """ - export RAYON_NUM_THREADS={threads} {manysearch_cmd} -k 31 --scaled=1000 -o {output.csv} \ - {input.queries} {input.against} + {input.queries} {input.against} -c {threads} """ rule a_vs_a_sub: @@ -62,9 +60,8 @@ rule a_vs_a_sub: "benchmarks/a_vs_a_{n}.txt" threads: 32 shell: """ - export RAYON_NUM_THREADS={threads} {manysearch_cmd} -k 31 --scaled=1000 -o {output.csv} \ - {input.queries} {input.against} + {input.queries} {input.against} -c {threads} """ rule a_vs_b: @@ -79,9 +76,8 @@ rule a_vs_b: "benchmarks/a_vs_b.txt" threads: 32 shell: """ - export RAYON_NUM_THREADS={threads} {manysearch_cmd} -k 31 --scaled=1000 -o {output.csv} \ - {input.queries} {input.against} + {input.queries} {input.against} -c {threads} """ rule a_vs_c: @@ -96,9 +92,8 @@ rule a_vs_c: "benchmarks/a_vs_c.txt" threads: 32 shell: """ - export RAYON_NUM_THREADS={threads} {manysearch_cmd} -k 31 --scaled=1000 -o {output.csv} \ - {input.queries} {input.against} + {input.queries} {input.against} -c {threads} """ rule a_vs_d: @@ -113,9 +108,8 @@ rule a_vs_d: "benchmarks/a_vs_d.txt" threads: 32 shell: """ - export RAYON_NUM_THREADS={threads} {manysearch_cmd} -k 31 --scaled=1000 -o {output.csv} \ - {input.queries} {input.against} + {input.queries} {input.against} -c {threads} """ rule a_vs_e: @@ -130,9 +124,8 @@ rule a_vs_e: "benchmarks/a_vs_e.txt" threads: 32 shell: """ - export RAYON_NUM_THREADS={threads} {manysearch_cmd} -k 31 --scaled=1000 -o {output.csv} \ - {input.queries} {input.against} + {input.queries} {input.against} -c {threads} """ rule a_vs_largest: @@ -147,9 +140,8 @@ rule a_vs_largest: "benchmarks/a_vs_largest_10k.txt" threads: 32 shell: """ - export RAYON_NUM_THREADS={threads} {manysearch_cmd} -k 31 --scaled=1000 -o {output.csv} \ - {input.queries} {input.against} + {input.queries} {input.against} -c {threads} """ rule a_vs_a_sub_threads: @@ -164,9 +156,8 @@ rule a_vs_a_sub_threads: "benchmarks/a_vs_a_{n}_t{thr}.txt" threads: 64 # max out threads so nothing else running shell: """ - export RAYON_NUM_THREADS={wildcards.thr} {manysearch_cmd} -k 31 --scaled=1000 -o {output.csv} \ - {input.queries} {input.against} + {input.queries} {input.against} -c {wildcards.thr} """ @@ -182,7 +173,6 @@ rule a_vs_catalog: "benchmarks/a_vs_catalog.txt" threads: 32 shell: """ - export RAYON_NUM_THREADS={threads} {manysearch_cmd} -k 31 --scaled=1000 -o {output.csv} \ - {input.queries} {input.against} || true + {input.queries} {input.against} -c {threads} || true """ diff --git a/environment.yml b/environment.yml index fb57584..933dae4 100644 --- a/environment.yml +++ b/environment.yml @@ -10,4 +10,4 @@ dependencies: - rust - maturin>=1,<2 - pip: - - pyo3_branchwater>=0.5.1 + - pyo3_branchwater==0.6.1 From 1a3fe6aca74cf1c658395533dbd7611397d292bb Mon Sep 17 00:00:00 2001 From: "C. Titus Brown" Date: Tue, 29 Aug 2023 09:59:52 -0700 Subject: [PATCH 11/27] updated bench --- benchmarks/a_100_vs_a.txt | 2 +- benchmarks/a_200_vs_a.txt | 2 +- benchmarks/a_300_vs_a.txt | 2 +- benchmarks/a_400_vs_a.txt | 2 +- benchmarks/a_500_vs_a.txt | 2 +- benchmarks/a_600_vs_a.txt | 2 +- benchmarks/a_700_vs_a.txt | 2 +- benchmarks/a_800_vs_a.txt | 2 +- benchmarks/a_900_vs_a.txt | 2 +- benchmarks/a_vs_a.txt | 2 +- benchmarks/a_vs_a_1000.txt | 2 +- benchmarks/a_vs_a_1000_t16.txt | 2 +- benchmarks/a_vs_a_1000_t4.txt | 2 +- benchmarks/a_vs_a_1000_t8.txt | 2 +- benchmarks/a_vs_a_2000.txt | 2 +- benchmarks/a_vs_a_3000.txt | 2 +- benchmarks/a_vs_a_4000.txt | 2 +- benchmarks/a_vs_a_5000.txt | 2 +- benchmarks/a_vs_a_6000.txt | 2 +- benchmarks/a_vs_a_7000.txt | 2 +- benchmarks/a_vs_a_8000.txt | 2 +- benchmarks/a_vs_a_9000.txt | 2 +- benchmarks/a_vs_b.txt | 2 +- benchmarks/a_vs_c.txt | 2 +- benchmarks/a_vs_catalog.txt | 2 +- benchmarks/a_vs_d.txt | 2 +- benchmarks/a_vs_e.txt | 2 +- benchmarks/a_vs_largest_10k.txt | 2 +- 28 files changed, 28 insertions(+), 28 deletions(-) diff --git a/benchmarks/a_100_vs_a.txt b/benchmarks/a_100_vs_a.txt index 8ee8445..68bc75a 100644 --- a/benchmarks/a_100_vs_a.txt +++ b/benchmarks/a_100_vs_a.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -8046.1403 2:14:06 10401.48 58493.38 10403.37 10403.95 72282.79 7.61 378.65 30478.66 +600.8063 0:10:00 14732.45 21267.59 14615.98 14620.31 0.01 8.24 2379.52 14299.89 diff --git a/benchmarks/a_200_vs_a.txt b/benchmarks/a_200_vs_a.txt index 3d22303..4fd03ac 100644 --- a/benchmarks/a_200_vs_a.txt +++ b/benchmarks/a_200_vs_a.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -6634.0672 1:50:34 10220.22 55552.64 10231.77 10232.34 60197.02 16.52 454.59 30161.81 +652.8024 0:10:52 15158.36 22479.65 14919.01 14923.30 0.00 16.54 2315.08 15116.74 diff --git a/benchmarks/a_300_vs_a.txt b/benchmarks/a_300_vs_a.txt index f8d4027..db3f80c 100644 --- a/benchmarks/a_300_vs_a.txt +++ b/benchmarks/a_300_vs_a.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -6791.2807 1:53:11 10283.14 50499.57 10275.11 10275.26 57833.04 23.31 448.54 30472.00 +688.3763 0:11:28 14350.04 21521.45 14501.56 14505.92 0.00 23.97 2324.88 16007.57 diff --git a/benchmarks/a_400_vs_a.txt b/benchmarks/a_400_vs_a.txt index 26c066b..726fbb4 100644 --- a/benchmarks/a_400_vs_a.txt +++ b/benchmarks/a_400_vs_a.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -5399.0796 1:29:59 10114.58 46904.75 10116.12 10116.37 47400.44 29.00 562.59 30399.56 +657.4765 0:10:57 18378.81 26965.45 17962.34 17966.62 0.00 31.45 2575.65 16934.31 diff --git a/benchmarks/a_500_vs_a.txt b/benchmarks/a_500_vs_a.txt index ab7ca97..452a411 100644 --- a/benchmarks/a_500_vs_a.txt +++ b/benchmarks/a_500_vs_a.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -7236.9012 2:00:36 10306.49 58546.62 10235.79 10236.42 64539.15 35.26 446.27 32299.50 +675.8257 0:11:15 15105.68 20776.05 15626.83 15631.12 0.01 37.62 2647.93 17899.05 diff --git a/benchmarks/a_600_vs_a.txt b/benchmarks/a_600_vs_a.txt index 66d5737..c17edab 100644 --- a/benchmarks/a_600_vs_a.txt +++ b/benchmarks/a_600_vs_a.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -8307.0373 2:18:27 10262.73 54648.19 10253.57 10254.16 69524.23 42.31 404.21 33580.93 +775.0072 0:12:55 14575.46 20334.43 14950.77 14955.17 0.00 45.79 2440.03 18914.15 diff --git a/benchmarks/a_700_vs_a.txt b/benchmarks/a_700_vs_a.txt index 0bb70c4..54ccb0a 100644 --- a/benchmarks/a_700_vs_a.txt +++ b/benchmarks/a_700_vs_a.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -5935.0510 1:38:55 10436.12 51007.27 10450.90 10451.52 54838.95 50.85 562.69 33401.60 +751.2011 0:12:31 18513.38 24394.66 18375.63 18379.91 0.00 56.44 2616.67 19660.27 diff --git a/benchmarks/a_800_vs_a.txt b/benchmarks/a_800_vs_a.txt index 156c0da..88bd6a5 100644 --- a/benchmarks/a_800_vs_a.txt +++ b/benchmarks/a_800_vs_a.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -6634.9251 1:50:34 10577.44 45540.72 10551.79 10552.37 57337.78 58.04 527.36 34999.19 +783.5165 0:13:03 14754.23 22361.55 14833.44 14837.79 0.00 65.54 2639.75 20686.77 diff --git a/benchmarks/a_900_vs_a.txt b/benchmarks/a_900_vs_a.txt index fcaaf56..d629b8b 100644 --- a/benchmarks/a_900_vs_a.txt +++ b/benchmarks/a_900_vs_a.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -6092.0311 1:41:32 10244.95 45939.66 10276.76 10277.33 52401.86 66.00 595.16 36253.98 +807.1810 0:13:27 18012.00 24211.34 17882.16 17886.44 0.01 72.65 2673.99 21584.14 diff --git a/benchmarks/a_vs_a.txt b/benchmarks/a_vs_a.txt index 6a458c4..967284e 100644 --- a/benchmarks/a_vs_a.txt +++ b/benchmarks/a_vs_a.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -6410.4036 1:46:50 10456.73 46762.75 10474.48 10474.75 54614.34 73.48 586.18 37592.65 +875.6504 0:14:35 18036.04 24671.35 17774.06 17778.36 0.00 82.84 2567.74 22488.25 diff --git a/benchmarks/a_vs_a_1000.txt b/benchmarks/a_vs_a_1000.txt index 31706a2..a952f18 100644 --- a/benchmarks/a_vs_a_1000.txt +++ b/benchmarks/a_vs_a_1000.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -190.5965 0:03:10 7835.11 13411.27 7682.85 7684.71 23.64 6.94 1537.50 2934.33 +128.7141 0:02:08 7857.28 13580.94 7753.30 7757.58 0.00 7.86 1526.84 1968.99 diff --git a/benchmarks/a_vs_a_1000_t16.txt b/benchmarks/a_vs_a_1000_t16.txt index 13e626a..7d75032 100644 --- a/benchmarks/a_vs_a_1000_t16.txt +++ b/benchmarks/a_vs_a_1000_t16.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -241.8623 0:04:01 4217.00 13616.37 4178.51 4181.75 0.00 7.04 1126.57 2729.88 +191.4212 0:03:11 6044.67 14880.95 6076.89 6090.70 0.00 7.91 1018.62 1956.75 diff --git a/benchmarks/a_vs_a_1000_t4.txt b/benchmarks/a_vs_a_1000_t4.txt index 722b4f2..876c08a 100644 --- a/benchmarks/a_vs_a_1000_t4.txt +++ b/benchmarks/a_vs_a_1000_t4.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -635.5993 0:10:35 2276.08 10742.91 2258.54 2263.37 0.00 7.33 376.03 2394.75 +560.6648 0:09:20 2803.79 11262.21 2790.16 2795.00 0.00 8.13 347.01 1952.88 diff --git a/benchmarks/a_vs_a_1000_t8.txt b/benchmarks/a_vs_a_1000_t8.txt index 6fda201..bb454ca 100644 --- a/benchmarks/a_vs_a_1000_t8.txt +++ b/benchmarks/a_vs_a_1000_t8.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -366.8955 0:06:06 3893.58 13670.58 3891.74 3894.74 106.28 7.14 658.99 2422.29 +291.7664 0:04:51 3481.41 11885.39 3448.68 3462.75 0.00 8.00 679.32 1988.99 diff --git a/benchmarks/a_vs_a_2000.txt b/benchmarks/a_vs_a_2000.txt index c450788..36eac01 100644 --- a/benchmarks/a_vs_a_2000.txt +++ b/benchmarks/a_vs_a_2000.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -492.1393 0:08:12 9266.73 19072.92 9177.62 9178.36 2893.39 14.18 1306.44 6433.30 +182.4287 0:03:02 10165.68 17257.38 10114.44 10118.73 0.00 16.05 2143.11 3913.24 diff --git a/benchmarks/a_vs_a_3000.txt b/benchmarks/a_vs_a_3000.txt index ff3210c..9a9449a 100644 --- a/benchmarks/a_vs_a_3000.txt +++ b/benchmarks/a_vs_a_3000.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -337.1346 0:05:37 9214.48 14774.27 8796.72 8800.22 221.05 21.63 2495.44 8417.19 +255.9341 0:04:15 10565.33 16437.94 10245.39 10249.78 0.01 24.18 2371.27 6072.81 diff --git a/benchmarks/a_vs_a_4000.txt b/benchmarks/a_vs_a_4000.txt index 1a45f86..16c21e1 100644 --- a/benchmarks/a_vs_a_4000.txt +++ b/benchmarks/a_vs_a_4000.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -1816.7844 0:30:16 10261.88 28934.04 10212.58 10213.18 17020.83 28.87 762.82 13863.96 +338.4716 0:05:38 12050.80 16843.22 11950.77 11955.05 0.00 32.11 2468.33 8358.54 diff --git a/benchmarks/a_vs_a_5000.txt b/benchmarks/a_vs_a_5000.txt index 0078c22..e87f319 100644 --- a/benchmarks/a_vs_a_5000.txt +++ b/benchmarks/a_vs_a_5000.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -4308.3585 1:11:48 10222.42 39749.15 10243.16 10243.61 40409.38 36.60 447.18 19284.64 +523.5476 0:08:43 14703.90 21026.22 14647.26 14651.61 0.00 40.57 2116.40 11084.23 diff --git a/benchmarks/a_vs_a_6000.txt b/benchmarks/a_vs_a_6000.txt index 5e876be..bd18e32 100644 --- a/benchmarks/a_vs_a_6000.txt +++ b/benchmarks/a_vs_a_6000.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -630.2757 0:10:30 14661.50 21440.07 11802.65 11805.98 56128.57 43.01 2918.98 18401.39 +480.6425 0:08:00 17173.78 22992.17 16840.85 16845.15 0.01 48.84 2719.14 13071.86 diff --git a/benchmarks/a_vs_a_7000.txt b/benchmarks/a_vs_a_7000.txt index 8547906..6cbecb6 100644 --- a/benchmarks/a_vs_a_7000.txt +++ b/benchmarks/a_vs_a_7000.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -4486.2303 1:14:46 10387.06 41859.28 10400.46 10401.07 40213.93 51.11 578.58 25962.25 +546.2705 0:09:06 15370.99 21318.24 15225.82 15230.17 0.00 56.76 2780.64 15193.29 diff --git a/benchmarks/a_vs_a_8000.txt b/benchmarks/a_vs_a_8000.txt index cbcb13e..11f3d87 100644 --- a/benchmarks/a_vs_a_8000.txt +++ b/benchmarks/a_vs_a_8000.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -5241.6019 1:27:21 10062.63 46267.62 10062.45 10062.98 0.00 0.00 565.28 29627.37 +618.4300 0:10:18 21471.61 27889.91 20961.72 20966.02 0.00 65.14 2820.35 17445.65 diff --git a/benchmarks/a_vs_a_9000.txt b/benchmarks/a_vs_a_9000.txt index b1b0084..ea92ebd 100644 --- a/benchmarks/a_vs_a_9000.txt +++ b/benchmarks/a_vs_a_9000.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -5638.5937 1:33:58 10485.32 43337.22 10510.07 10510.71 49704.38 66.75 577.80 32585.03 +665.4772 0:11:05 17767.80 24126.63 17617.10 17621.45 0.01 74.00 2964.38 19731.08 diff --git a/benchmarks/a_vs_b.txt b/benchmarks/a_vs_b.txt index 5319a37..3833544 100644 --- a/benchmarks/a_vs_b.txt +++ b/benchmarks/a_vs_b.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -10972.9724 3:02:52 10129.77 56932.70 10109.43 10110.02 84926.57 72.73 331.31 36359.01 +827.8913 0:13:47 16330.66 22992.92 16727.98 16732.33 0.01 79.96 2671.40 22116.21 diff --git a/benchmarks/a_vs_c.txt b/benchmarks/a_vs_c.txt index 2f860ed..d45a9bd 100644 --- a/benchmarks/a_vs_c.txt +++ b/benchmarks/a_vs_c.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -6546.8879 1:49:06 10403.43 52091.42 10226.46 10227.06 59158.95 73.10 530.59 34751.04 +759.2550 0:12:39 17084.92 22578.64 16849.08 16853.45 0.01 82.22 2845.20 21602.36 diff --git a/benchmarks/a_vs_catalog.txt b/benchmarks/a_vs_catalog.txt index fbb34be..6917e81 100644 --- a/benchmarks/a_vs_catalog.txt +++ b/benchmarks/a_vs_catalog.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -11909.1569 3:18:29 10413.05 90798.36 10404.97 10405.67 95900.80 187.55 738.36 87945.42 +56864.2508 15:47:44 35820.05 44126.49 35512.32 35517.34 78.45 6359.39 3016.27 1715185.69 diff --git a/benchmarks/a_vs_d.txt b/benchmarks/a_vs_d.txt index 5854eab..3cc6e9e 100644 --- a/benchmarks/a_vs_d.txt +++ b/benchmarks/a_vs_d.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -8474.0678 2:21:14 10509.81 55628.16 10474.58 10475.17 74463.39 72.83 430.85 36527.69 +807.2910 0:13:27 15190.04 20914.19 15028.30 15032.68 0.00 82.21 2735.69 22088.67 diff --git a/benchmarks/a_vs_e.txt b/benchmarks/a_vs_e.txt index e467e28..2c02433 100644 --- a/benchmarks/a_vs_e.txt +++ b/benchmarks/a_vs_e.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -6643.4003 1:50:43 10399.51 47443.64 10452.64 10453.31 57368.30 76.80 530.69 35255.88 +743.7042 0:12:23 17108.77 22594.65 17374.48 17378.82 0.00 84.39 2892.58 21516.02 diff --git a/benchmarks/a_vs_largest_10k.txt b/benchmarks/a_vs_largest_10k.txt index a125ffa..deb8269 100644 --- a/benchmarks/a_vs_largest_10k.txt +++ b/benchmarks/a_vs_largest_10k.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -25440.2672 7:04:00 54988.84 68716.06 47801.98 47806.76 2225582.01 181.20 3044.02 774410.78 +19046.7232 5:17:26 60354.86 76403.62 61956.32 61960.61 111.21 204.75 2979.81 567559.73 From de4c94ae60e6f00f096081b8445ecb2a14c6c4c9 Mon Sep 17 00:00:00 2001 From: "C. Titus Brown" Date: Tue, 29 Aug 2023 10:00:06 -0700 Subject: [PATCH 12/27] more bench --- README.md | 2 +- benchmarking.snakefile | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 12702ed..a634d55 100644 --- a/README.md +++ b/README.md @@ -15,7 +15,7 @@ srun -p high2 --time=72:00:00 --nodes=1 --cpus-per-task 64 --mem 80GB --pty bash then run the snakemake workflow: ``` -snakemake -c 64 -p -s benchmarking.snakefile --resources only_one_job=1 +snakemake -c 64 -p -s benchmarking.snakefile --resources only_one_job=1 -k ``` ## appendix diff --git a/benchmarking.snakefile b/benchmarking.snakefile index e89afae..c60bde4 100644 --- a/benchmarking.snakefile +++ b/benchmarking.snakefile @@ -13,7 +13,7 @@ rule all: rule threads: input: - expand("benchmarks/a_vs_a_1000_t{t}.txt", t=[4,8,16]), + expand("benchmarks/a_vs_a_1000_t{t}.txt", t=[4,8,16,24,32,40,48,56,64]), rule a_vs_a: From bbb050431c14713ab8de753e332910f304ac9c55 Mon Sep 17 00:00:00 2001 From: "C. Titus Brown" Date: Fri, 1 Sep 2023 11:02:48 -0700 Subject: [PATCH 13/27] update pyo3_branchwater 0.7.0 --- environment.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/environment.yml b/environment.yml index 933dae4..76cfdf0 100644 --- a/environment.yml +++ b/environment.yml @@ -10,4 +10,4 @@ dependencies: - rust - maturin>=1,<2 - pip: - - pyo3_branchwater==0.6.1 + - pyo3_branchwater==0.7.0 From d5c60e3f014dd4c3bfe1692f5536bec7e70189df Mon Sep 17 00:00:00 2001 From: "C. Titus Brown" Date: Fri, 1 Sep 2023 11:03:11 -0700 Subject: [PATCH 14/27] split up smk --- benchmarking.snakefile | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/benchmarking.snakefile b/benchmarking.snakefile index c60bde4..74b1f0b 100644 --- a/benchmarking.snakefile +++ b/benchmarking.snakefile @@ -5,11 +5,14 @@ rule all: input: expand("benchmarks/{x}_vs_{y}.txt", x=['a'], y=['a', 'b', 'c', 'd', 'e']), + +rule big: + input: + expand("benchmarks/a_vs_a_1000_t{t}.txt", t=[4,8,16]), "outputs/output_a_vs_largest_10k.csv", + expand("benchmarks/a_vs_catalog.txt"), expand("benchmarks/a_{n}_vs_a.txt", n=range(100, 1000, 100)), expand("benchmarks/a_vs_a_{n}.txt", n=range(1000, 10000, 1000)), - expand("benchmarks/a_vs_a_1000_t{t}.txt", t=[4,8,16]), - expand("benchmarks/a_vs_catalog.txt"), rule threads: input: From b8f83134b1d8121e714a283f1805d1b375165d1b Mon Sep 17 00:00:00 2001 From: "C. Titus Brown" Date: Sat, 2 Sep 2023 07:45:25 -0700 Subject: [PATCH 15/27] add summarization script --- benchmarking.snakefile | 2 ++ benchmarks/a_vs_a.txt | 2 +- benchmarks/a_vs_b.txt | 2 +- benchmarks/a_vs_c.txt | 2 +- benchmarks/a_vs_d.txt | 2 +- benchmarks/a_vs_e.txt | 2 +- summarize.py | 20 ++++++++++++++++++++ 7 files changed, 27 insertions(+), 5 deletions(-) create mode 100644 summarize.py diff --git a/benchmarking.snakefile b/benchmarking.snakefile index 74b1f0b..8b66d3e 100644 --- a/benchmarking.snakefile +++ b/benchmarking.snakefile @@ -5,6 +5,8 @@ rule all: input: expand("benchmarks/{x}_vs_{y}.txt", x=['a'], y=['a', 'b', 'c', 'd', 'e']), + expand("outputs/output_{x}_vs_{y}.csv", x=['a'], + y=['a', 'b', 'c', 'd', 'e']), rule big: input: diff --git a/benchmarks/a_vs_a.txt b/benchmarks/a_vs_a.txt index 967284e..12090d4 100644 --- a/benchmarks/a_vs_a.txt +++ b/benchmarks/a_vs_a.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -875.6504 0:14:35 18036.04 24671.35 17774.06 17778.36 0.00 82.84 2567.74 22488.25 +919.6511 0:15:19 17597.27 24031.18 17298.20 17302.42 0.00 102.35 2633.43 24221.92 diff --git a/benchmarks/a_vs_b.txt b/benchmarks/a_vs_b.txt index 3833544..c7a6430 100644 --- a/benchmarks/a_vs_b.txt +++ b/benchmarks/a_vs_b.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -827.8913 0:13:47 16330.66 22992.92 16727.98 16732.33 0.01 79.96 2671.40 22116.21 +933.1807 0:15:33 17187.03 24217.97 16875.07 16879.28 0.00 0.00 2548.04 23730.38 diff --git a/benchmarks/a_vs_c.txt b/benchmarks/a_vs_c.txt index d45a9bd..737fc8d 100644 --- a/benchmarks/a_vs_c.txt +++ b/benchmarks/a_vs_c.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -759.2550 0:12:39 17084.92 22578.64 16849.08 16853.45 0.01 82.22 2845.20 21602.36 +847.8818 0:14:07 15040.67 21140.09 14697.48 14701.73 0.00 102.20 2710.66 22987.35 diff --git a/benchmarks/a_vs_d.txt b/benchmarks/a_vs_d.txt index 3cc6e9e..e7cc281 100644 --- a/benchmarks/a_vs_d.txt +++ b/benchmarks/a_vs_d.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -807.2910 0:13:27 15190.04 20914.19 15028.30 15032.68 0.00 82.21 2735.69 22088.67 +841.7877 0:14:01 18019.69 24126.99 17811.66 17815.86 0.00 101.58 2829.97 23825.85 diff --git a/benchmarks/a_vs_e.txt b/benchmarks/a_vs_e.txt index 2c02433..2393c1b 100644 --- a/benchmarks/a_vs_e.txt +++ b/benchmarks/a_vs_e.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -743.7042 0:12:23 17108.77 22594.65 17374.48 17378.82 0.00 84.39 2892.58 21516.02 +992.2560 0:16:32 13746.12 19312.14 14108.83 14113.00 0.00 104.90 2323.13 23054.95 diff --git a/summarize.py b/summarize.py new file mode 100644 index 0000000..577ed46 --- /dev/null +++ b/summarize.py @@ -0,0 +1,20 @@ +import pandas as pd + +def load_benchmark_replicate(filename, ident): + df = pd.read_csv(filename, sep='\t') + df['ident'] = ident + + return df + +print("reading from benchmarks/a_vs_{x}.txt...") +replicates_df = [ load_benchmark_replicate(f"benchmarks/a_vs_{x}.txt", x) for x in ('a','b','c','d','e')] +#query_line.append(load_benchmark_and_annotate('benchmarks/a_vs_a.txt', 1000, 10000)) +replicates_df = pd.concat(replicates_df) +replicates_df + +replicates_df['m'] = replicates_df['s'] / 60.0 +print(f"mean time (minutes) {replicates_df.m.mean():.1f} +/- {replicates_df.m.std():.1f}") + +print(f"mean RSS (GB) {replicates_df.max_rss.mean()/1000:.1f} +/- {replicates_df.max_rss.std()/1000:.1f}") + +print(f"mean I/O (kb) {replicates_df.io_in.mean():.1f} +/- {replicates_df.io_in.std():.1f}") From e9c2ccb87cb37655403af04a35d6695f3ce0c5e9 Mon Sep 17 00:00:00 2001 From: "C. Titus Brown" Date: Mon, 30 Sep 2024 16:49:32 -0700 Subject: [PATCH 16/27] benchmarks for v0.8.9 pr 430 --- benchmarks/a_100_vs_a.txt | 2 -- benchmarks/a_200_vs_a.txt | 2 -- benchmarks/a_300_vs_a.txt | 2 -- benchmarks/a_400_vs_a.txt | 2 -- benchmarks/a_500_vs_a.txt | 2 -- benchmarks/a_600_vs_a.txt | 2 -- benchmarks/a_700_vs_a.txt | 2 -- benchmarks/a_800_vs_a.txt | 2 -- benchmarks/a_900_vs_a.txt | 2 -- benchmarks/a_vs_a.txt | 2 +- benchmarks/a_vs_a_1000.txt | 2 -- benchmarks/a_vs_a_1000_t16.txt | 2 -- benchmarks/a_vs_a_1000_t4.txt | 2 -- benchmarks/a_vs_a_1000_t8.txt | 2 -- benchmarks/a_vs_a_2000.txt | 2 -- benchmarks/a_vs_a_3000.txt | 2 -- benchmarks/a_vs_a_4000.txt | 2 -- benchmarks/a_vs_a_5000.txt | 2 -- benchmarks/a_vs_a_6000.txt | 2 -- benchmarks/a_vs_a_7000.txt | 2 -- benchmarks/a_vs_a_8000.txt | 2 -- benchmarks/a_vs_a_9000.txt | 2 -- benchmarks/a_vs_b.txt | 2 +- benchmarks/a_vs_c.txt | 2 +- benchmarks/a_vs_catalog.txt | 2 -- benchmarks/a_vs_d.txt | 2 +- benchmarks/a_vs_e.txt | 2 +- benchmarks/a_vs_largest_10k.txt | 2 -- 28 files changed, 5 insertions(+), 51 deletions(-) delete mode 100644 benchmarks/a_100_vs_a.txt delete mode 100644 benchmarks/a_200_vs_a.txt delete mode 100644 benchmarks/a_300_vs_a.txt delete mode 100644 benchmarks/a_400_vs_a.txt delete mode 100644 benchmarks/a_500_vs_a.txt delete mode 100644 benchmarks/a_600_vs_a.txt delete mode 100644 benchmarks/a_700_vs_a.txt delete mode 100644 benchmarks/a_800_vs_a.txt delete mode 100644 benchmarks/a_900_vs_a.txt delete mode 100644 benchmarks/a_vs_a_1000.txt delete mode 100644 benchmarks/a_vs_a_1000_t16.txt delete mode 100644 benchmarks/a_vs_a_1000_t4.txt delete mode 100644 benchmarks/a_vs_a_1000_t8.txt delete mode 100644 benchmarks/a_vs_a_2000.txt delete mode 100644 benchmarks/a_vs_a_3000.txt delete mode 100644 benchmarks/a_vs_a_4000.txt delete mode 100644 benchmarks/a_vs_a_5000.txt delete mode 100644 benchmarks/a_vs_a_6000.txt delete mode 100644 benchmarks/a_vs_a_7000.txt delete mode 100644 benchmarks/a_vs_a_8000.txt delete mode 100644 benchmarks/a_vs_a_9000.txt delete mode 100644 benchmarks/a_vs_catalog.txt delete mode 100644 benchmarks/a_vs_largest_10k.txt diff --git a/benchmarks/a_100_vs_a.txt b/benchmarks/a_100_vs_a.txt deleted file mode 100644 index 68bc75a..0000000 --- a/benchmarks/a_100_vs_a.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -600.8063 0:10:00 14732.45 21267.59 14615.98 14620.31 0.01 8.24 2379.52 14299.89 diff --git a/benchmarks/a_200_vs_a.txt b/benchmarks/a_200_vs_a.txt deleted file mode 100644 index 4fd03ac..0000000 --- a/benchmarks/a_200_vs_a.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -652.8024 0:10:52 15158.36 22479.65 14919.01 14923.30 0.00 16.54 2315.08 15116.74 diff --git a/benchmarks/a_300_vs_a.txt b/benchmarks/a_300_vs_a.txt deleted file mode 100644 index db3f80c..0000000 --- a/benchmarks/a_300_vs_a.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -688.3763 0:11:28 14350.04 21521.45 14501.56 14505.92 0.00 23.97 2324.88 16007.57 diff --git a/benchmarks/a_400_vs_a.txt b/benchmarks/a_400_vs_a.txt deleted file mode 100644 index 726fbb4..0000000 --- a/benchmarks/a_400_vs_a.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -657.4765 0:10:57 18378.81 26965.45 17962.34 17966.62 0.00 31.45 2575.65 16934.31 diff --git a/benchmarks/a_500_vs_a.txt b/benchmarks/a_500_vs_a.txt deleted file mode 100644 index 452a411..0000000 --- a/benchmarks/a_500_vs_a.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -675.8257 0:11:15 15105.68 20776.05 15626.83 15631.12 0.01 37.62 2647.93 17899.05 diff --git a/benchmarks/a_600_vs_a.txt b/benchmarks/a_600_vs_a.txt deleted file mode 100644 index c17edab..0000000 --- a/benchmarks/a_600_vs_a.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -775.0072 0:12:55 14575.46 20334.43 14950.77 14955.17 0.00 45.79 2440.03 18914.15 diff --git a/benchmarks/a_700_vs_a.txt b/benchmarks/a_700_vs_a.txt deleted file mode 100644 index 54ccb0a..0000000 --- a/benchmarks/a_700_vs_a.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -751.2011 0:12:31 18513.38 24394.66 18375.63 18379.91 0.00 56.44 2616.67 19660.27 diff --git a/benchmarks/a_800_vs_a.txt b/benchmarks/a_800_vs_a.txt deleted file mode 100644 index 88bd6a5..0000000 --- a/benchmarks/a_800_vs_a.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -783.5165 0:13:03 14754.23 22361.55 14833.44 14837.79 0.00 65.54 2639.75 20686.77 diff --git a/benchmarks/a_900_vs_a.txt b/benchmarks/a_900_vs_a.txt deleted file mode 100644 index d629b8b..0000000 --- a/benchmarks/a_900_vs_a.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -807.1810 0:13:27 18012.00 24211.34 17882.16 17886.44 0.01 72.65 2673.99 21584.14 diff --git a/benchmarks/a_vs_a.txt b/benchmarks/a_vs_a.txt index 12090d4..3374284 100644 --- a/benchmarks/a_vs_a.txt +++ b/benchmarks/a_vs_a.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -919.6511 0:15:19 17597.27 24031.18 17298.20 17302.42 0.00 102.35 2633.43 24221.92 +15003.8397 4:10:03 19116.10 25746.33 12790.69 12799.04 173947.26 162.15 2478.24 371838.10 diff --git a/benchmarks/a_vs_a_1000.txt b/benchmarks/a_vs_a_1000.txt deleted file mode 100644 index a952f18..0000000 --- a/benchmarks/a_vs_a_1000.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -128.7141 0:02:08 7857.28 13580.94 7753.30 7757.58 0.00 7.86 1526.84 1968.99 diff --git a/benchmarks/a_vs_a_1000_t16.txt b/benchmarks/a_vs_a_1000_t16.txt deleted file mode 100644 index 7d75032..0000000 --- a/benchmarks/a_vs_a_1000_t16.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -191.4212 0:03:11 6044.67 14880.95 6076.89 6090.70 0.00 7.91 1018.62 1956.75 diff --git a/benchmarks/a_vs_a_1000_t4.txt b/benchmarks/a_vs_a_1000_t4.txt deleted file mode 100644 index 876c08a..0000000 --- a/benchmarks/a_vs_a_1000_t4.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -560.6648 0:09:20 2803.79 11262.21 2790.16 2795.00 0.00 8.13 347.01 1952.88 diff --git a/benchmarks/a_vs_a_1000_t8.txt b/benchmarks/a_vs_a_1000_t8.txt deleted file mode 100644 index bb454ca..0000000 --- a/benchmarks/a_vs_a_1000_t8.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -291.7664 0:04:51 3481.41 11885.39 3448.68 3462.75 0.00 8.00 679.32 1988.99 diff --git a/benchmarks/a_vs_a_2000.txt b/benchmarks/a_vs_a_2000.txt deleted file mode 100644 index 36eac01..0000000 --- a/benchmarks/a_vs_a_2000.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -182.4287 0:03:02 10165.68 17257.38 10114.44 10118.73 0.00 16.05 2143.11 3913.24 diff --git a/benchmarks/a_vs_a_3000.txt b/benchmarks/a_vs_a_3000.txt deleted file mode 100644 index 9a9449a..0000000 --- a/benchmarks/a_vs_a_3000.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -255.9341 0:04:15 10565.33 16437.94 10245.39 10249.78 0.01 24.18 2371.27 6072.81 diff --git a/benchmarks/a_vs_a_4000.txt b/benchmarks/a_vs_a_4000.txt deleted file mode 100644 index 16c21e1..0000000 --- a/benchmarks/a_vs_a_4000.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -338.4716 0:05:38 12050.80 16843.22 11950.77 11955.05 0.00 32.11 2468.33 8358.54 diff --git a/benchmarks/a_vs_a_5000.txt b/benchmarks/a_vs_a_5000.txt deleted file mode 100644 index e87f319..0000000 --- a/benchmarks/a_vs_a_5000.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -523.5476 0:08:43 14703.90 21026.22 14647.26 14651.61 0.00 40.57 2116.40 11084.23 diff --git a/benchmarks/a_vs_a_6000.txt b/benchmarks/a_vs_a_6000.txt deleted file mode 100644 index bd18e32..0000000 --- a/benchmarks/a_vs_a_6000.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -480.6425 0:08:00 17173.78 22992.17 16840.85 16845.15 0.01 48.84 2719.14 13071.86 diff --git a/benchmarks/a_vs_a_7000.txt b/benchmarks/a_vs_a_7000.txt deleted file mode 100644 index 6cbecb6..0000000 --- a/benchmarks/a_vs_a_7000.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -546.2705 0:09:06 15370.99 21318.24 15225.82 15230.17 0.00 56.76 2780.64 15193.29 diff --git a/benchmarks/a_vs_a_8000.txt b/benchmarks/a_vs_a_8000.txt deleted file mode 100644 index 11f3d87..0000000 --- a/benchmarks/a_vs_a_8000.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -618.4300 0:10:18 21471.61 27889.91 20961.72 20966.02 0.00 65.14 2820.35 17445.65 diff --git a/benchmarks/a_vs_a_9000.txt b/benchmarks/a_vs_a_9000.txt deleted file mode 100644 index ea92ebd..0000000 --- a/benchmarks/a_vs_a_9000.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -665.4772 0:11:05 17767.80 24126.63 17617.10 17621.45 0.01 74.00 2964.38 19731.08 diff --git a/benchmarks/a_vs_b.txt b/benchmarks/a_vs_b.txt index c7a6430..0f219eb 100644 --- a/benchmarks/a_vs_b.txt +++ b/benchmarks/a_vs_b.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -933.1807 0:15:33 17187.03 24217.97 16875.07 16879.28 0.00 0.00 2548.04 23730.38 +13551.7736 3:45:51 20020.86 24514.55 14336.73 14345.03 163062.66 156.71 2702.21 366204.22 diff --git a/benchmarks/a_vs_c.txt b/benchmarks/a_vs_c.txt index 737fc8d..6b08b0f 100644 --- a/benchmarks/a_vs_c.txt +++ b/benchmarks/a_vs_c.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -847.8818 0:14:07 15040.67 21140.09 14697.48 14701.73 0.00 102.20 2710.66 22987.35 +12197.0952 3:23:17 18300.29 22527.06 12091.51 12098.92 134246.69 161.84 2897.81 353455.94 diff --git a/benchmarks/a_vs_catalog.txt b/benchmarks/a_vs_catalog.txt deleted file mode 100644 index 6917e81..0000000 --- a/benchmarks/a_vs_catalog.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -56864.2508 15:47:44 35820.05 44126.49 35512.32 35517.34 78.45 6359.39 3016.27 1715185.69 diff --git a/benchmarks/a_vs_d.txt b/benchmarks/a_vs_d.txt index e7cc281..3807173 100644 --- a/benchmarks/a_vs_d.txt +++ b/benchmarks/a_vs_d.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -841.7877 0:14:01 18019.69 24126.99 17811.66 17815.86 0.00 101.58 2829.97 23825.85 +13227.8901 3:40:27 24182.67 29365.75 14625.86 14634.22 173289.28 160.97 2766.24 365922.36 diff --git a/benchmarks/a_vs_e.txt b/benchmarks/a_vs_e.txt index 2393c1b..67473f9 100644 --- a/benchmarks/a_vs_e.txt +++ b/benchmarks/a_vs_e.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -992.2560 0:16:32 13746.12 19312.14 14108.83 14113.00 0.00 104.90 2323.13 23054.95 +13670.4617 3:47:50 16581.98 24003.19 10497.51 10503.60 148365.68 166.09 2588.26 353833.68 diff --git a/benchmarks/a_vs_largest_10k.txt b/benchmarks/a_vs_largest_10k.txt deleted file mode 100644 index deb8269..0000000 --- a/benchmarks/a_vs_largest_10k.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -19046.7232 5:17:26 60354.86 76403.62 61956.32 61960.61 111.21 204.75 2979.81 567559.73 From 6520e58f7f48fc5b7ac5032fa4ab159be8ee9a52 Mon Sep 17 00:00:00 2001 From: "C. Titus Brown" Date: Tue, 1 Oct 2024 06:06:18 -0700 Subject: [PATCH 17/27] 0.9.7 benchmarks --- benchmarks/a_vs_a.txt | 2 -- benchmarks/a_vs_b.txt | 2 -- benchmarks/a_vs_c.txt | 2 -- benchmarks/a_vs_d.txt | 2 +- benchmarks/a_vs_e.txt | 2 +- 5 files changed, 2 insertions(+), 8 deletions(-) delete mode 100644 benchmarks/a_vs_a.txt delete mode 100644 benchmarks/a_vs_b.txt delete mode 100644 benchmarks/a_vs_c.txt diff --git a/benchmarks/a_vs_a.txt b/benchmarks/a_vs_a.txt deleted file mode 100644 index 3374284..0000000 --- a/benchmarks/a_vs_a.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -15003.8397 4:10:03 19116.10 25746.33 12790.69 12799.04 173947.26 162.15 2478.24 371838.10 diff --git a/benchmarks/a_vs_b.txt b/benchmarks/a_vs_b.txt deleted file mode 100644 index 0f219eb..0000000 --- a/benchmarks/a_vs_b.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -13551.7736 3:45:51 20020.86 24514.55 14336.73 14345.03 163062.66 156.71 2702.21 366204.22 diff --git a/benchmarks/a_vs_c.txt b/benchmarks/a_vs_c.txt deleted file mode 100644 index 6b08b0f..0000000 --- a/benchmarks/a_vs_c.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -12197.0952 3:23:17 18300.29 22527.06 12091.51 12098.92 134246.69 161.84 2897.81 353455.94 diff --git a/benchmarks/a_vs_d.txt b/benchmarks/a_vs_d.txt index 3807173..7e6b3ab 100644 --- a/benchmarks/a_vs_d.txt +++ b/benchmarks/a_vs_d.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -13227.8901 3:40:27 24182.67 29365.75 14625.86 14634.22 173289.28 160.97 2766.24 365922.36 +17080.8594 4:44:40 20271.94 27300.93 14017.28 14024.89 163102.85 160.94 2664.55 455132.35 diff --git a/benchmarks/a_vs_e.txt b/benchmarks/a_vs_e.txt index 67473f9..7e9d0d0 100644 --- a/benchmarks/a_vs_e.txt +++ b/benchmarks/a_vs_e.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -13670.4617 3:47:50 16581.98 24003.19 10497.51 10503.60 148365.68 166.09 2588.26 353833.68 +15367.7230 4:16:07 22232.73 28768.41 13165.15 13171.65 152042.78 166.18 2819.02 433223.17 From 140e3b0cc489fa2f21e7914d1a202e151444cb39 Mon Sep 17 00:00:00 2001 From: "C. Titus Brown" Date: Tue, 1 Oct 2024 06:52:56 -0700 Subject: [PATCH 18/27] bench with v0.8.6 --- benchmarks/a_vs_d.txt | 2 +- benchmarks/a_vs_e.txt | 2 -- 2 files changed, 1 insertion(+), 3 deletions(-) delete mode 100644 benchmarks/a_vs_e.txt diff --git a/benchmarks/a_vs_d.txt b/benchmarks/a_vs_d.txt index 7e6b3ab..c0ec14c 100644 --- a/benchmarks/a_vs_d.txt +++ b/benchmarks/a_vs_d.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -17080.8594 4:44:40 20271.94 27300.93 14017.28 14024.89 163102.85 160.94 2664.55 455132.35 +814.2453 0:13:34 18362.10 24765.34 13155.76 13163.25 73732.36 101.79 2911.80 23713.75 diff --git a/benchmarks/a_vs_e.txt b/benchmarks/a_vs_e.txt deleted file mode 100644 index 7e9d0d0..0000000 --- a/benchmarks/a_vs_e.txt +++ /dev/null @@ -1,2 +0,0 @@ -s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -15367.7230 4:16:07 22232.73 28768.41 13165.15 13171.65 152042.78 166.18 2819.02 433223.17 From 33fcefe70885e3b650024ad46f6acc3e167dd5d8 Mon Sep 17 00:00:00 2001 From: "C. Titus Brown" Date: Tue, 1 Oct 2024 07:26:49 -0700 Subject: [PATCH 19/27] v0.9.0 benchmarks --- benchmarks/a_vs_d.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/benchmarks/a_vs_d.txt b/benchmarks/a_vs_d.txt index c0ec14c..3696e6e 100644 --- a/benchmarks/a_vs_d.txt +++ b/benchmarks/a_vs_d.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -814.2453 0:13:34 18362.10 24765.34 13155.76 13163.25 73732.36 101.79 2911.80 23713.75 +1332.0061 0:22:12 19842.16 27100.33 14953.86 14961.27 138859.82 100.53 2804.41 37359.93 From 25d198dc9ca281005e3e6649ef646d1b3403e38e Mon Sep 17 00:00:00 2001 From: "C. Titus Brown" Date: Tue, 1 Oct 2024 08:05:47 -0700 Subject: [PATCH 20/27] benchmark with 0.9.1 --- benchmarks/a_vs_d.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/benchmarks/a_vs_d.txt b/benchmarks/a_vs_d.txt index 3696e6e..55d04ef 100644 --- a/benchmarks/a_vs_d.txt +++ b/benchmarks/a_vs_d.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -1332.0061 0:22:12 19842.16 27100.33 14953.86 14961.27 138859.82 100.53 2804.41 37359.93 +1361.2095 0:22:41 22472.57 30269.09 13681.01 13688.41 114142.62 100.50 2853.18 38841.14 From 22e1fdca3c0ce795bad81b90959e76ef653686fa Mon Sep 17 00:00:00 2001 From: "C. Titus Brown" Date: Tue, 1 Oct 2024 08:43:17 -0700 Subject: [PATCH 21/27] plugin v0.9.5 bench --- benchmarks/a_vs_d.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/benchmarks/a_vs_d.txt b/benchmarks/a_vs_d.txt index 55d04ef..94b4a50 100644 --- a/benchmarks/a_vs_d.txt +++ b/benchmarks/a_vs_d.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -1361.2095 0:22:41 22472.57 30269.09 13681.01 13688.41 114142.62 100.50 2853.18 38841.14 +1534.3187 0:25:34 21071.59 29992.09 16288.37 16295.87 107886.18 136.15 2856.54 43832.62 From 2ec47225885bc6e1cc538756a9d597af4692bcb2 Mon Sep 17 00:00:00 2001 From: "C. Titus Brown" Date: Wed, 2 Oct 2024 13:13:23 -0700 Subject: [PATCH 22/27] bench --- benchmarking.snakefile | 2 +- benchmarks/a_vs_d.txt | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/benchmarking.snakefile b/benchmarking.snakefile index 8b66d3e..b22977c 100644 --- a/benchmarking.snakefile +++ b/benchmarking.snakefile @@ -1,5 +1,5 @@ #sra_search_bin="/home/ctbrown/scratch/magsearch/bin/searcher" -manysearch_cmd = "sourmash scripts manysearch" +manysearch_cmd = "sourmash scripts manysearch --ignore-abundance" rule all: input: diff --git a/benchmarks/a_vs_d.txt b/benchmarks/a_vs_d.txt index 94b4a50..3d8c95b 100644 --- a/benchmarks/a_vs_d.txt +++ b/benchmarks/a_vs_d.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -1534.3187 0:25:34 21071.59 29992.09 16288.37 16295.87 107886.18 136.15 2856.54 43832.62 +14012.2358 3:53:32 20720.34 27658.48 14301.84 14318.82 129136.86 135.93 2673.04 374556.12 From f11681947109b674036c573eacb225c58dd455c1 Mon Sep 17 00:00:00 2001 From: "C. Titus Brown" Date: Fri, 4 Oct 2024 16:24:44 -0700 Subject: [PATCH 23/27] upd --- benchmarks/a_vs_d.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/benchmarks/a_vs_d.txt b/benchmarks/a_vs_d.txt index 3d8c95b..16485f3 100644 --- a/benchmarks/a_vs_d.txt +++ b/benchmarks/a_vs_d.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -14012.2358 3:53:32 20720.34 27658.48 14301.84 14318.82 129136.86 135.93 2673.04 374556.12 +14854.6904 4:07:34 20268.02 27422.25 13784.42 13791.87 164666.21 136.09 2451.25 364129.42 From 829e97e2b2baebf27d86cf83e24d354b10170dc8 Mon Sep 17 00:00:00 2001 From: "C. Titus Brown" Date: Sat, 5 Oct 2024 16:16:34 -0700 Subject: [PATCH 24/27] fixed --- benchmarking.snakefile | 1 + benchmarks/a_vs_d.txt | 2 +- 2 files changed, 2 insertions(+), 1 deletion(-) diff --git a/benchmarking.snakefile b/benchmarking.snakefile index b22977c..5df0656 100644 --- a/benchmarking.snakefile +++ b/benchmarking.snakefile @@ -1,4 +1,5 @@ #sra_search_bin="/home/ctbrown/scratch/magsearch/bin/searcher" +#manysearch_cmd = "sourmash scripts manysearch " manysearch_cmd = "sourmash scripts manysearch --ignore-abundance" rule all: diff --git a/benchmarks/a_vs_d.txt b/benchmarks/a_vs_d.txt index 16485f3..f47b173 100644 --- a/benchmarks/a_vs_d.txt +++ b/benchmarks/a_vs_d.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -14854.6904 4:07:34 20268.02 27422.25 13784.42 13791.87 164666.21 136.09 2451.25 364129.42 +1388.6216 0:23:08 20510.26 29471.41 15790.74 15797.76 6.31 135.94 2789.85 38743.45 From f19671a2bd58f30b1958f028533c559d17e118a4 Mon Sep 17 00:00:00 2001 From: "C. Titus Brown" Date: Sat, 5 Oct 2024 19:51:46 -0700 Subject: [PATCH 25/27] upd with 464 --- benchmarking.snakefile | 4 ++-- benchmarks/a_vs_d.txt | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/benchmarking.snakefile b/benchmarking.snakefile index 5df0656..489d096 100644 --- a/benchmarking.snakefile +++ b/benchmarking.snakefile @@ -1,6 +1,6 @@ #sra_search_bin="/home/ctbrown/scratch/magsearch/bin/searcher" -#manysearch_cmd = "sourmash scripts manysearch " -manysearch_cmd = "sourmash scripts manysearch --ignore-abundance" +manysearch_cmd = "sourmash scripts manysearch " +#manysearch_cmd = "sourmash scripts manysearch --ignore-abundance" rule all: input: diff --git a/benchmarks/a_vs_d.txt b/benchmarks/a_vs_d.txt index f47b173..e6efa0b 100644 --- a/benchmarks/a_vs_d.txt +++ b/benchmarks/a_vs_d.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -1388.6216 0:23:08 20510.26 29471.41 15790.74 15797.76 6.31 135.94 2789.85 38743.45 +1428.0000 0:23:48 18609.89 23561.79 15977.05 15985.64 6.61 160.97 2778.06 39678.49 From 31d3675e4c0044413bc6a730ed223e48fdab9a0c Mon Sep 17 00:00:00 2001 From: "C. Titus Brown" Date: Sun, 13 Oct 2024 10:11:58 -0700 Subject: [PATCH 26/27] bench --- benchmarks/a_vs_d.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/benchmarks/a_vs_d.txt b/benchmarks/a_vs_d.txt index e6efa0b..5cad7fb 100644 --- a/benchmarks/a_vs_d.txt +++ b/benchmarks/a_vs_d.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -1428.0000 0:23:48 18609.89 23561.79 15977.05 15985.64 6.61 160.97 2778.06 39678.49 +1096.6601 0:18:16 16459.99 23673.26 15953.61 15960.90 155362.78 160.83 2736.99 30019.85 From 9f593f3b7e264a00398c96b98a73a7700be06a6c Mon Sep 17 00:00:00 2001 From: "C. Titus Brown" Date: Sun, 13 Oct 2024 10:29:12 -0700 Subject: [PATCH 27/27] use manifest CSVs --- benchmarking.snakefile | 2 +- benchmarks/a_vs_d.txt | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/benchmarking.snakefile b/benchmarking.snakefile index 489d096..9ee9fe0 100644 --- a/benchmarking.snakefile +++ b/benchmarking.snakefile @@ -105,7 +105,7 @@ rule a_vs_c: rule a_vs_d: input: queries="data/gtdb-list-a.sigs.txt", - against="data/wort-list-d.txt", + against="wort-list.d.mf.csv", output: csv="outputs/output_a_vs_d.csv", resources: diff --git a/benchmarks/a_vs_d.txt b/benchmarks/a_vs_d.txt index 5cad7fb..4daff89 100644 --- a/benchmarks/a_vs_d.txt +++ b/benchmarks/a_vs_d.txt @@ -1,2 +1,2 @@ s h:m:s max_rss max_vms max_uss max_pss io_in io_out mean_load cpu_time -1096.6601 0:18:16 16459.99 23673.26 15953.61 15960.90 155362.78 160.83 2736.99 30019.85 +559.7348 0:09:19 38303.28 110077.33 38193.48 38200.80 34302.56 160.97 2433.26 13623.33