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[QST]Why is cuml GPU dozens of times slower than scikit-learn CPU in Lasso,Ridge and ElasticNet models? #6080

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JiayuChen02 opened this issue Sep 24, 2024 · 2 comments
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? - Needs Triage Need team to review and classify question Further information is requested

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@JiayuChen02
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I tried to compare the speed difference of the same model on CPU and GPU. Here is my code:

import numpy as np
import pandas as pd
import time
import cudf
import cupy as cp
from cuml.linear_model import Lasso as cuml_model
from sklearn.linear_model import Lasso as sk_model

n_samples = 300 
n_features = 120000  

X = np.random.rand(n_samples, n_features)
y = np.random.rand(n_samples)


param = {
    "alpha": 0.001,
    "max_iter": 1000,
    "tol": 1e-3,
}

sklearn_model = sk_model()
sklearn_model.set_params(**param)

start_time = time.time()
sklearn_model.fit(X, y)
end_time = time.time()

print(sklearn_model.get_params())

print(f"scikit-learn training time: {end_time - start_time:.4f} seconds")


X_cudf = cp.array(X)
y_cudf = cp.array(y)


rapids_model = cuml_model()
rapids_model.set_params(**param)

start_time = time.time()

rapids_model.fit(X_cudf, y_cudf)

end_time = time.time()
print(rapids_model.get_params())
print(f"cuML GPU training time: {end_time - start_time:.4f} seconds")

And the result is

{'alpha': 0.001, 'copy_X': True, 'fit_intercept': True, 'max_iter': 1000, 'positive': False, 'precompute': False, 'random_state': None, 'selection': 'cyclic', 'tol': 0.001, 'warm_start': False}
scikit-learn training time: 14.0172 seconds
{'selection': 'cyclic', 'solver': 'cd', 'tol': 0.001, 'output_type': 'input', 'normalize': False, 'handle': <pylibraft.common.handle.Handle object at 0x7fa5b99e02d0>, 'alpha': 0.001, 'fit_intercept': True, 'verbose': 4, 'max_iter': 1000}
cuML GPU training time: 486.6329 seconds

Why?

@JiayuChen02 JiayuChen02 added ? - Needs Triage Need team to review and classify question Further information is requested labels Sep 24, 2024
@dantegd
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dantegd commented Sep 24, 2024

Thanks for the issue @JiayuChen02, I just tried your code on a machine with a T4 and this is the results I got:

{'alpha': 0.001, 'copy_X': True, 'fit_intercept': True, 'max_iter': 1000, 'positive': False, 'precompute': False, 'random_state': None, 'selection': 'cyclic', 'tol': 0.001, 'warm_start': False}
scikit-learn training time: 7.7504 seconds
{'output_type': 'input', 'verbose': 4, 'handle': <pylibraft.common.handle.Handle object at 0x7fd8addf73f0>, 'fit_intercept': True, 'normalize': False, 'tol': 0.001, 'solver': 'cd', 'max_iter': 1000, 'alpha': 0.001, 'selection': 'cyclic'}
cuML GPU training time: 0.8425 seconds

In general, 300 rows is not a dataset where I would expect massive GPU speedups, but things seem to be working fine. What could be happening is you could be running maybe into some JIT compilation issues? What GPU are you using? It would be very helpful if you could run this script and put the output here: https://github.com/rapidsai/cuml/blob/branch-24.10/print_env.sh

@JiayuChen02
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JiayuChen02 commented Sep 25, 2024

Thanks for the issue @JiayuChen02, I just tried your code on a machine with a T4 and this is the results I got:

{'alpha': 0.001, 'copy_X': True, 'fit_intercept': True, 'max_iter': 1000, 'positive': False, 'precompute': False, 'random_state': None, 'selection': 'cyclic', 'tol': 0.001, 'warm_start': False}
scikit-learn training time: 7.7504 seconds
{'output_type': 'input', 'verbose': 4, 'handle': <pylibraft.common.handle.Handle object at 0x7fd8addf73f0>, 'fit_intercept': True, 'normalize': False, 'tol': 0.001, 'solver': 'cd', 'max_iter': 1000, 'alpha': 0.001, 'selection': 'cyclic'}
cuML GPU training time: 0.8425 seconds

In general, 300 rows is not a dataset where I would expect massive GPU speedups, but things seem to be working fine. What could be happening is you could be running maybe into some JIT compilation issues? What GPU are you using? It would be very helpful if you could run this script and put the output here: https://github.com/rapidsai/cuml/blob/branch-24.10/print_env.sh

@dantegd Thanks for your reply. This is the output of print_env.sh

Click here to see environment details
 **git***
 Not inside a git repository

 ***OS Information***
 DISTRIB_ID=Ubuntu
 DISTRIB_RELEASE=22.04
 DISTRIB_CODENAME=jammy
 DISTRIB_DESCRIPTION="Ubuntu 22.04.4 LTS"
 PRETTY_NAME="Ubuntu 22.04.4 LTS"
 NAME="Ubuntu"
 VERSION_ID="22.04"
 VERSION="22.04.4 LTS (Jammy Jellyfish)"
 VERSION_CODENAME=jammy
 ID=ubuntu
 ID_LIKE=debian
 HOME_URL="https://www.ubuntu.com/"
 SUPPORT_URL="https://help.ubuntu.com/"
 BUG_REPORT_URL="https://bugs.launchpad.net/ubuntu/"
 PRIVACY_POLICY_URL="https://www.ubuntu.com/legal/terms-and-policies/privacy-policy"
 UBUNTU_CODENAME=jammy
 Linux 6eae716c1e8c 5.4.0-100-generic #113-Ubuntu SMP Thu Feb 3 18:43:29 UTC 2022 x86_64 x86_64 x86_64 GNU/Linux

GPU Information
Wed Sep 25 01:13:48 2024
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 555.42.02 Driver Version: 555.42.02 CUDA Version: 12.5 |
|-----------------------------------------+------------------------+----------------------+
| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|=========================================+========================+======================|
| 0 NVIDIA A100 80GB PCIe Off | 00000000:17:00.0 Off | 0 |
| N/A 35C P0 63W / 300W | 989MiB / 81920MiB | 0% Default |
| | | Disabled |
+-----------------------------------------+------------------------+----------------------+
| 1 NVIDIA A100 80GB PCIe Off | 00000000:CA:00.0 Off | 0 |
| N/A 34C P0 43W / 300W | 4MiB / 81920MiB | 0% Default |
| | | Disabled |
+-----------------------------------------+------------------------+----------------------+

 +-----------------------------------------------------------------------------------------+
 | Processes:                                                                              |
 |  GPU   GI   CI        PID   Type   Process name                              GPU Memory |
 |        ID   ID                                                               Usage      |
 |=========================================================================================|
 +-----------------------------------------------------------------------------------------+

CPU
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Address sizes: 46 bits physical, 57 bits virtual
Byte Order: Little Endian
CPU(s): 104
On-line CPU(s) list: 0-103
Vendor ID: GenuineIntel
Model name: Intel(R) Xeon(R) Gold 5320 CPU @ 2.20GHz
CPU family: 6
Model: 106
Thread(s) per core: 2
Core(s) per socket: 26
Socket(s): 2
Stepping: 6
BogoMIPS: 4400.00
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 invpcid_single ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local wbnoinvd dtherm ida arat pln pts avx512vbmi umip pku ospke avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq rdpid md_clear pconfig flush_l1d arch_capabilities

Virtualization: VT-x
L1d cache: 2.4 MiB (52 instances)
L1i cache: 1.6 MiB (52 instances)
L2 cache: 65 MiB (52 instances)
L3 cache: 78 MiB (2 instances)
NUMA node(s): 2
NUMA node0 CPU(s): 0,2,4,6,8,10,12,14,16,18,20,22,24,26,28,30,32,34,36,38,40,42,44,46,48,50,52,54,56,58,60,62,64,66,68,70,72,74,76,78,80,82,84,86,88,90,92,94,96,98,100,102
NUMA node1 CPU(s): 1,3,5,7,9,11,13,15,17,19,21,23,25,27,29,31,33,35,37,39,41,43,45,47,49,51,53,55,57,59,61,63,65,67,69,71,73,75,77,79,81,83,85,87,89,91,93,95,97,99,101,103
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; Enhanced IBRS, IBPB conditional, RSB filling
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected

 ***CMake***

g++

 ***nvcc***
 /opt/conda/bin/nvcc
 nvcc: NVIDIA (R) Cuda compiler driver
 Copyright (c) 2005-2024 NVIDIA Corporation
 Built on Thu_Jun__6_02:18:23_PDT_2024
 Cuda compilation tools, release 12.5, V12.5.82
 Build cuda_12.5.r12.5/compiler.34385749_0

 ***Python***
 /opt/conda/bin/python
 Python 3.9.19

 ***Environment Variables***
 PATH                            : /opt/conda/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
 LD_LIBRARY_PATH                 : /usr/local/nvidia/lib:/usr/local/nvidia/lib64
 NUMBAPRO_NVVM                   :
 NUMBAPRO_LIBDEVICE              :
 CONDA_PREFIX                    :
 PYTHON_PATH                     :  

conda packages
/opt/conda/bin/conda
# packages in environment at /opt/conda:
#
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libcudf_kafka 24.08.02 cuda12_240814_ge776742c28_0 rapidsai
libcufft 11.2.3.61 he02047a_0 conda-forge
libcufile 1.10.1.7 he02047a_0 conda-forge
libcufile-dev 1.10.1.7 he02047a_0 conda-forge
libcugraph 24.08.00 cuda12_240808_gfc880db0c_0 rapidsai
libcugraph_etl 24.08.00 cuda12_240808_gfc880db0c_0 rapidsai
libcugraphops 24.08.01 cuda12_240808_gefdc8f56_0 rapidsai
libcuml 24.08.00 cuda12_240808_gb17f2dbbe_0 rapidsai
libcumlprims 24.08.00 cuda12_240808_g172c6cb_0 rapidsai
libcurand 10.3.6.82 he02047a_0 conda-forge
libcurand-dev 10.3.6.82 he02047a_0 conda-forge
libcurl 8.9.1 hdb1bdb2_0 conda-forge
libcusolver 11.6.3.83 he02047a_0 conda-forge
libcusolver-dev 11.6.3.83 he02047a_0 conda-forge
libcusparse 12.5.1.3 he02047a_0 conda-forge
libcusparse-dev 12.5.1.3 he02047a_0 conda-forge
libcuspatial 24.08.00 cuda12_240808_g601ae02f_0 rapidsai
libcuvs 24.08.00 cuda12_240808_g8f250ac_0 rapidsai
libdeflate 1.19 hd590300_0 conda-forge
libedit 3.1.20191231 he28a2e2_2 conda-forge
libev 4.33 hd590300_2 conda-forge
libevent 2.1.12 hf998b51_1 conda-forge
libexpat 2.6.2 h59595ed_0 conda-forge
libffi 3.4.2 h7f98852_5 conda-forge
libgcc-ng 14.1.0 h77fa898_0 conda-forge
libgdal 3.8.1 h4b8bffa_3 conda-forge
libgettextpo 0.22.5 he02047a_3 conda-forge
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libgfortran-ng 14.1.0 h69a702a_0 conda-forge
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libglib 2.78.4 h783c2da_0 conda-forge
libgomp 14.1.0 h77fa898_0 conda-forge
libgoogle-cloud 2.28.0 h26d7fe4_0 conda-forge
libgoogle-cloud-storage 2.28.0 ha262f82_0 conda-forge
libgrpc 1.62.2 h15f2491_0 conda-forge
libiconv 1.17 hd590300_2 conda-forge
libjpeg-turbo 3.0.0 hd590300_1 conda-forge
libkml 1.3.0 hbbc8833_1020 conda-forge
libkvikio 24.08.02 cuda12_240807_g6b80a5c_0 rapidsai
liblapack 3.9.0 23_linux64_openblas conda-forge
libllvm14 14.0.6 hcd5def8_4 conda-forge
libmamba 1.5.8 had39da4_0 conda-forge
libmambapy 1.5.8 py39h10defb6_0 conda-forge
libnetcdf 4.9.2 nompi_h135f659_114 conda-forge
libnghttp2 1.58.0 h47da74e_1 conda-forge
libnl 3.10.0 h4bc722e_0 conda-forge
libnsl 2.0.1 hd590300_0 conda-forge
libntlm 1.4 h7f98852_1002 conda-forge
libnvjitlink 12.5.82 he02047a_0 conda-forge
libnvjpeg 12.3.2.81 he02047a_0 conda-forge
libopenblas 0.3.27 pthreads_hac2b453_1 conda-forge
libparquet 16.1.0 haa1307c_20_cpu conda-forge
libpng 1.6.43 h2797004_0 conda-forge
libpq 16.4 h482b261_0 conda-forge
libprotobuf 4.25.3 h08a7969_0 conda-forge
libraft 24.08.01 cuda12_240807_g185da16b_0 rapidsai
libraft-headers 24.08.01 cuda12_240807_g185da16b_0 rapidsai
libraft-headers-only 24.08.01 cuda12_240807_g185da16b_0 rapidsai
librdkafka 1.9.2 ha5a0de0_2 conda-forge
libre2-11 2023.09.01 h5a48ba9_2 conda-forge
librmm 24.08.02 cuda12_240807_g5aa8ebe6_0 rapidsai
librttopo 1.1.0 h8917695_15 conda-forge
libsodium 1.0.18 h36c2ea0_1 conda-forge
libsolv 0.7.30 h3509ff9_0 conda-forge
libspatialite 5.1.0 h72606ae_3 conda-forge
libsqlite 3.46.0 hde9e2c9_0 conda-forge
libssh2 1.11.0 h0841786_0 conda-forge
libstdcxx-ng 14.1.0 hc0a3c3a_0 conda-forge
libthrift 0.20.0 hb90f79a_0 conda-forge
libtiff 4.6.0 ha9c0a0a_2 conda-forge
libucxx 0.39.01 cuda12_240807_g19a66b4_0 rapidsai
libutf8proc 2.8.0 h166bdaf_0 conda-forge
libuuid 2.38.1 h0b41bf4_0 conda-forge
libuv 1.48.0 hd590300_0 conda-forge
libwebp-base 1.4.0 hd590300_0 conda-forge
libxcb 1.15 h0b41bf4_0 conda-forge
libxcrypt 4.4.36 hd590300_1 conda-forge
libxgboost 2.1.1 rapidsai_h207c33c_4 rapidsai
libxml2 2.12.7 h4c95cb1_3 conda-forge
libzip 1.10.1 h2629f0a_3 conda-forge
libzlib 1.3.1 h4ab18f5_1 conda-forge
linkify-it-py 2.0.3 pyhd8ed1ab_0 conda-forge
llvmlite 0.43.0 py39h81bab63_0 conda-forge
locket 1.0.0 pyhd8ed1ab_0 conda-forge
lz4 4.3.3 py39h79d96da_0 conda-forge
lz4-c 1.9.4 hcb278e6_0 conda-forge
lzo 2.10 hd590300_1001 conda-forge
mamba 1.5.8 py39hc5d2bb1_0 conda-forge
mapclassify 2.8.0 pyhd8ed1ab_0 conda-forge
markdown 3.6 pyhd8ed1ab_0 conda-forge
markdown-it-py 3.0.0 pyhd8ed1ab_0 conda-forge
markupsafe 2.1.5 py39hd1e30aa_0 conda-forge
matplotlib-base 3.9.1 py39h0565ad7_2 conda-forge
matplotlib-inline 0.1.7 pyhd8ed1ab_0 conda-forge
mdit-py-plugins 0.4.1 pyhd8ed1ab_0 conda-forge
mdurl 0.1.2 pyhd8ed1ab_0 conda-forge
menuinst 2.1.2 py39hf3d152e_0 conda-forge
minizip 4.0.7 h401b404_0 conda-forge
mistune 3.0.2 pyhd8ed1ab_0 conda-forge
msgpack-python 1.0.8 py39h95fdab5_0 conda-forge
multidict 6.0.5 py39hd1e30aa_0 conda-forge
multipledispatch 0.6.0 pyhd8ed1ab_1 conda-forge
munkres 1.1.4 pyh9f0ad1d_0 conda-forge
nbclient 0.10.0 pyhd8ed1ab_0 conda-forge
nbconvert-core 7.16.4 pyhd8ed1ab_1 conda-forge
nbformat 5.10.4 pyhd8ed1ab_0 conda-forge
nccl 2.22.3.1 hbc370b7_1 conda-forge
ncurses 6.5 h59595ed_0 conda-forge
networkx 3.2.1 pyhd8ed1ab_0 conda-forge
nodejs 22.6.0 h6d9b948_0 conda-forge
nspr 4.35 h27087fc_0 conda-forge
nss 3.103 h593d115_0 conda-forge
numba 0.60.0 py39h0320e7d_0 conda-forge
numexpr 2.10.1 pypi_0 pypi
numpy 1.26.4 py39h474f0d3_0 conda-forge
nvcomp 3.0.6 h10b603f_0 conda-forge
nvtx 0.2.10 py39hd1e30aa_0 conda-forge
nx-cugraph 24.08.00 py39_0 rapidsai
openjpeg 2.5.2 h488ebb8_0 conda-forge
openssl 3.3.1 h4bc722e_2 conda-forge
orc 2.0.1 h17fec99_1 conda-forge
osqp 0.6.7.post1 pypi_0 pypi
overrides 7.7.0 pyhd8ed1ab_0 conda-forge
packaging 24.1 pyhd8ed1ab_0 conda-forge
pandas 2.2.2 py39hfc16268_1 conda-forge
pandocfilters 1.5.0 pyhd8ed1ab_0 conda-forge
panel 1.4.5 pyhd8ed1ab_0 conda-forge
param 2.1.1 pyhff2d567_0 conda-forge
parso 0.8.4 pyhd8ed1ab_0 conda-forge
partd 1.4.2 pyhd8ed1ab_0 conda-forge
pcre2 10.42 hcad00b1_0 conda-forge
pexpect 4.9.0 pyhd8ed1ab_0 conda-forge
pickleshare 0.7.5 py_1003 conda-forge
pillow 10.3.0 py39h90c7501_0 conda-forge
pip 24.2 pyhd8ed1ab_0 conda-forge
pixman 0.43.2 h59595ed_0 conda-forge
pkgutil-resolve-name 1.3.10 pyhd8ed1ab_1 conda-forge
platformdirs 4.2.2 pyhd8ed1ab_0 conda-forge
pluggy 1.5.0 pyhd8ed1ab_0 conda-forge
poppler 23.12.0 h590f24d_0 conda-forge
poppler-data 0.4.12 hd8ed1ab_0 conda-forge
postgresql 16.4 ha8faf9a_0 conda-forge
proj 9.3.0 h1d62c97_2 conda-forge
prometheus_client 0.20.0 pyhd8ed1ab_0 conda-forge
prompt-toolkit 3.0.47 pyha770c72_0 conda-forge
psutil 6.0.0 py39hd3abc70_0 conda-forge
pthread-stubs 0.4 h36c2ea0_1001 conda-forge
ptyprocess 0.7.0 pyhd3deb0d_0 conda-forge
pure_eval 0.2.3 pyhd8ed1ab_0 conda-forge
py-xgboost 2.1.1 rapidsai_pyhf7e6b63_4 rapidsai
pyaml 24.7.0 pypi_0 pypi
pyarrow 16.1.0 py39he8689d4_5 conda-forge
pyarrow-core 16.1.0 py39hb8ba4b6_5_cpu conda-forge
pyarrow-hotfix 0.6 pyhd8ed1ab_0 conda-forge
pybind11-abi 4 hd8ed1ab_3 conda-forge
pycosat 0.6.6 py39hd1e30aa_0 conda-forge
pycparser 2.22 pyhd8ed1ab_0 conda-forge
pyct 0.5.0 pyhd8ed1ab_0 conda-forge
pyee 8.1.0 pyhd8ed1ab_0 conda-forge
pygments 2.18.0 pyhd8ed1ab_0 conda-forge
pylibcugraph 24.08.00 cuda12_py39_240808_gfc880db0c_0 rapidsai
pylibraft 24.08.01 cuda12_py39_240807_g185da16b_0 rapidsai
pynvjitlink 0.3.0 py39hd269673_0 rapidsai
pynvml 11.4.1 pyhd8ed1ab_0 conda-forge
pyogrio 0.7.2 py39hcfcd403_1 conda-forge
pyparsing 3.1.2 pyhd8ed1ab_0 conda-forge
pyppeteer 1.0.2 pyhd8ed1ab_0 conda-forge
pyproj 3.6.1 py39hce394fd_4 conda-forge
pysocks 1.7.1 pyha2e5f31_6 conda-forge
python 3.9.19 h0755675_0_cpython conda-forge
python-confluent-kafka 1.9.2 py39hb9d737c_2 conda-forge
python-dateutil 2.9.0 pyhd8ed1ab_0 conda-forge
python-fastjsonschema 2.20.0 pyhd8ed1ab_0 conda-forge
python-json-logger 2.0.7 pyhd8ed1ab_0 conda-forge
python-tzdata 2024.1 pyhd8ed1ab_0 conda-forge
python_abi 3.9 4_cp39 conda-forge
pytz 2024.1 pyhd8ed1ab_0 conda-forge
pyviz_comms 3.0.3 pyhd8ed1ab_0 conda-forge
pywavelets 1.6.0 py39hd92a3bb_0 conda-forge
pyyaml 6.0.2 py39hcd6043d_0 conda-forge
pyzmq 26.1.0 py39hbdd323a_0 conda-forge
qdldl 0.1.7.post4 pypi_0 pypi
qhull 2020.2 h434a139_5 conda-forge
raft-dask 24.08.01 cuda12_py39_240807_g185da16b_0 rapidsai
rapids 24.08.00 cuda12_py39_240808_g86654f0_0 rapidsai
rapids-dask-dependency 24.08.00 py_0 rapidsai
rapids-xgboost 24.08.00 cuda12_py39_240808_g86654f0_0 rapidsai
rdma-core 53.0 he02047a_0 conda-forge
re2 2023.09.01 h7f4b329_2 conda-forge
readline 8.2 h8228510_1 conda-forge
referencing 0.35.1 pyhd8ed1ab_0 conda-forge
reproc 14.2.4.post0 hd590300_1 conda-forge
reproc-cpp 14.2.4.post0 h59595ed_1 conda-forge
requests 2.32.3 pyhd8ed1ab_0 conda-forge
rfc3339-validator 0.1.4 pyhd8ed1ab_0 conda-forge
rfc3986-validator 0.1.1 pyh9f0ad1d_0 conda-forge
rich 13.7.1 pyhd8ed1ab_0 conda-forge
rmm 24.08.02 cuda12_py39_240807_g5aa8ebe6_0 rapidsai
rpds-py 0.20.0 py39h5cde264_0 conda-forge
ruamel.yaml 0.18.6 py39hd1e30aa_0 conda-forge
ruamel.yaml.clib 0.2.8 py39hd1e30aa_0 conda-forge
s2n 1.5.0 h3400bea_0 conda-forge
scikit-image 0.19.3 py39h4661b88_2 conda-forge
scikit-learn 1.5.1 py39hf7b0125_0 conda-forge
scikit-optimize 0.10.2 pypi_0 pypi
scikit-survival 0.23.0 pypi_0 pypi
scipy 1.13.1 py39haf93ffa_0 conda-forge
send2trash 1.8.3 pyh0d859eb_0 conda-forge
setuptools 72.1.0 pyhd8ed1ab_0 conda-forge
shapely 2.0.4 py39h5a575da_1 conda-forge
simpervisor 1.0.0 pyhd8ed1ab_0 conda-forge
six 1.16.0 pyh6c4a22f_0 conda-forge
snappy 1.2.1 ha2e4443_0 conda-forge
sniffio 1.3.1 pyhd8ed1ab_0 conda-forge
sortedcontainers 2.4.0 pyhd8ed1ab_0 conda-forge
soupsieve 2.5 pyhd8ed1ab_1 conda-forge
spdlog 1.12.0 hd2e6256_2 conda-forge
sqlite 3.46.0 h6d4b2fc_0 conda-forge
stack_data 0.6.2 pyhd8ed1ab_0 conda-forge
streamz 0.6.4 pyh6c4a22f_0 conda-forge
tblib 3.0.0 pyhd8ed1ab_0 conda-forge
terminado 0.18.1 pyh0d859eb_0 conda-forge
threadpoolctl 3.5.0 pyhc1e730c_0 conda-forge
tifffile 2020.6.3 py_0 conda-forge
tiledb 2.18.2 h99f50a1_1 conda-forge
tinycss2 1.3.0 pyhd8ed1ab_0 conda-forge
tk 8.6.13 noxft_h4845f30_101 conda-forge
toolz 0.12.1 pyhd8ed1ab_0 conda-forge
tornado 6.4.1 py39hd3abc70_0 conda-forge
tqdm 4.66.5 pyhd8ed1ab_0 conda-forge
traitlets 5.14.3 pyhd8ed1ab_0 conda-forge
treelite 4.3.0 py39hcb22a9e_0 conda-forge
types-python-dateutil 2.9.0.20240316 pyhd8ed1ab_0 conda-forge
typing-extensions 4.12.2 hd8ed1ab_0 conda-forge
typing_extensions 4.12.2 pyha770c72_0 conda-forge
typing_utils 0.1.0 pyhd8ed1ab_0 conda-forge
tzcode 2024a h3f72095_0 conda-forge
tzdata 2024a h0c530f3_0 conda-forge
uc-micro-py 1.0.3 pyhd8ed1ab_0 conda-forge
ucx 1.15.0 hda83522_8 conda-forge
ucx-proc 1.0.0 gpu rapidsai
ucx-py 0.39.02 py39_240807_g314778e_0 rapidsai
ucxx 0.39.01 cuda12_py3.9_240807_g19a66b4_0 rapidsai
unicodedata2 15.1.0 py39hd1e30aa_0 conda-forge
uri-template 1.3.0 pyhd8ed1ab_0 conda-forge
uriparser 0.9.8 hac33072_0 conda-forge
urllib3 1.26.19 pyhd8ed1ab_0 conda-forge
wcwidth 0.2.13 pyhd8ed1ab_0 conda-forge
webcolors 24.8.0 pyhd8ed1ab_0 conda-forge
webencodings 0.5.1 pyhd8ed1ab_2 conda-forge
websocket-client 1.8.0 pyhd8ed1ab_0 conda-forge
websockets 10.4 py39hb9d737c_1 conda-forge
wheel 0.44.0 pyhd8ed1ab_0 conda-forge
xarray 2024.7.0 pyhd8ed1ab_0 conda-forge
xerces-c 3.2.5 hac6953d_0 conda-forge
xgboost 2.1.1 rapidsai_pyh26c0410_4 rapidsai
xorg-kbproto 1.0.7 h7f98852_1002 conda-forge
xorg-libice 1.1.1 hd590300_0 conda-forge
xorg-libsm 1.2.4 h7391055_0 conda-forge
xorg-libx11 1.8.9 h8ee46fc_0 conda-forge
xorg-libxau 1.0.11 hd590300_0 conda-forge
xorg-libxdmcp 1.1.3 h7f98852_0 conda-forge
xorg-libxext 1.3.4 h0b41bf4_2 conda-forge
xorg-libxrender 0.9.11 hd590300_0 conda-forge
xorg-renderproto 0.11.1 h7f98852_1002 conda-forge
xorg-xextproto 7.3.0 h0b41bf4_1003 conda-forge
xorg-xproto 7.0.31 h7f98852_1007 conda-forge
xyzservices 2024.6.0 pyhd8ed1ab_0 conda-forge
xz 5.2.6 h166bdaf_0 conda-forge
yaml 0.2.5 h7f98852_2 conda-forge
yaml-cpp 0.8.0 h59595ed_0 conda-forge
yarl 1.9.4 py39hd1e30aa_0 conda-forge
zeromq 4.3.5 h75354e8_4 conda-forge
zict 3.0.0 pyhd8ed1ab_0 conda-forge
zipp 3.20.0 pyhd8ed1ab_0 conda-forge
zlib 1.3.1 h4ab18f5_1 conda-forge
zstandard 0.23.0 py39h623c9ba_0 conda-forge
zstd 1.5.6 ha6fb4c9_0 conda-forge

Could you please help me see what the possible errors are and how I can fix them next?

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