[feat] Add HKV which is based on merlin HierarchicalHV

.github/workflows/make_wheel_Linux_x86.sh

@@ -13,7 +13,7 @@ fi
 
 # if tensorflow version >= 2.6.0 and <= 2.11.9
 if [[ "$TF_VERSION" =~ ^2\.([6-9]|10|11)\.[0-9]$ ]] ; then
-  export BUILD_IMAGE="tfra/nosla-cuda11.2.1-cudnn8-ubuntu20.04-manylinux2014-python$PY_VERSION"
+  export BUILD_IMAGE="tfra/nosla-cuda11.2.2-cudnn8-ubuntu20.04-manylinux2014-python$PY_VERSION"
   export TF_CUDA_VERSION="11.2"
   export TF_CUDNN_VERSION="8.1"
 elif [ $TF_VERSION == "2.4.1" ] ; then

WORKSPACE

@@ -54,6 +54,14 @@ http_archive(
     url = "https://github.com/sewenew/redis-plus-plus/archive/refs/tags/1.2.3.zip",
 )
 
+http_archive(
+    name = "hkv",
+    build_file = "//build_deps/toolchains/hkv:hkv.BUILD",
+    sha256 = "3839f91b703b401fd6d2449c034662b6f8d6563e5b9b71b4c25b217cf1cd63fd",
+    strip_prefix = "HierarchicalKV-0.1.0-beta.8",
+    url = "https://github.com/NVIDIA-Merlin/HierarchicalKV/archive/refs/tags/v0.1.0-beta.8.tar.gz",
+)
+
 tf_configure(
     name = "local_config_tf",
 )

build_deps/toolchains/gpu/cuda_configure.bzl

@@ -68,8 +68,6 @@ _DEFAULT_CUDA_COMPUTE_CAPABILITIES = {
 
 _DEFAULT_CUDA_COMPUTE_CAPABILITIES.update(
     {"11.{}".format(v): [
-        "6.0",
-        "6.1",
         "7.0",
         "7.5",
         "8.0",

build_deps/toolchains/hkv/hkv.BUILD

@@ -0,0 +1,18 @@
+load("@local_config_cuda//cuda:build_defs.bzl", "if_cuda", "if_cuda_is_configured")
+
+package(default_visibility = ["//visibility:public"])
+
+cc_library(
+    name = "hkv",
+    hdrs = glob([
+        "include/merlin/core_kernels/*.cuh",
+        "include/merlin/*.cuh",
+        "include/*.cuh",
+        "include/*.hpp",
+    ]),
+    copts = [
+        "-Ofast",
+    ],
+    include_prefix = "include",
+    includes = ["include"],
+)

docs/api_docs/tfra/dynamic_embedding.md

@@ -47,6 +47,12 @@ Export dynamic_embedding APIs.
 
 [`class ModelMode`](../tfra/dynamic_embedding/ModelMode.md): The global config of model modes.
 
+[`class HkvHashTable`](../tfra/dynamic_embedding/HkvHashTable.md): A generic mutable hash table implementation.
+
+[`class HkvHashTableConfig`](../tfra/dynamic_embedding/HkvHashTableConfig.md): HkvHashTableConfig config init_capacity, max_capacity, max_hbm_for_values of HkvHashTable
+
+[`class HkvHashTableCreator`](../tfra/dynamic_embedding/HkvHashTableCreator.md):   A generic KV table creator.
+
 [`class RedisTable`](../tfra/dynamic_embedding/RedisTable.md): A generic mutable hash table implementation.
 
 [`class RedisTableConfig`](../tfra/dynamic_embedding/RedisTableConfig.md): RedisTableConfig config json file for connecting Redis service and 

docs/api_docs/tfra/dynamic_embedding/CuckooHashTable.md

@@ -53,7 +53,8 @@ remove method. It does not support initialization via the init method.
 ```python
 table = tfra.dynamic_embedding.CuckooHashTable(key_dtype=tf.string,
                                                value_dtype=tf.int64,
-                                               default_value=-1)
+                                               default_value=-1,
+                                               device=['/GPU:0'])
 sess.run(table.insert(keys, values))
 out = table.lookup(query_keys)
 print(out.eval())
@@ -106,6 +107,10 @@ A `CuckooHashTable` object.
 * <b>`ValueError`</b>: If checkpoint is True and no name was specified.
 
 
+## <b>`Important update！！`</b>
+
+We have made updates to the underlying implementation of the CuckooHashTable. The original CPU table remains unchanged, but the GPU table now uses the HKV implementation instead of nvhash. To ensure interface consistency, the init_capacity and max_capacity of HKV will be set to the init_size value you pass in. It is important to note that after this setting, the GPU hash table will not automatically resize, and the final capacity will be the same as the init_size. The max_hbm_for_values parameter of hkv will be set to a sufficiently large number to ensure that all your data is stored in the GPU table. Additionally, hkv has requirements for GPU compute capability, which needs to be 8.0 or above. For more detailed information about HKV, please refer to the documentation of HKV.
+
 
 ## Properties
 

docs/api_docs/tfra/dynamic_embedding/CuckooHashTableCreator.md

@@ -41,13 +41,10 @@ class for creating the real KV table backend(TF resource).
 
 #### Example usage:
 
-
+Due to CuckooHashTableConfig include nothing for parameter default satisfied. Just setting the parameter saver is enough.
 
 ```python
-redis_config1=tfra.dynamic_embedding.RedisTableConfig(
-  redis_config_abs_dir="xx/yy.json"
-)
-redis_creator1=tfra.dynamic_embedding.RedisTableCreator(redis_config1)
+cuckoo_creator=tfra.dynamic_embedding.CuckooHashTableCreator(saver=de.FileSystemSaver())
 ```
 
 <h2 id="__init__"><code>__init__</code></h2>