Add a new concurrent hashmap benchmark to AI benchmark suite in DCPerf. #147
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…f. (facebookresearch#147) Summary: This update introduces a new benchmark type, CHM, to the AI benchmark suite. The CHM benchmark simulates the usage pattern of a concurrent hash map in machine learning workloads, where certain key-value pairs are hashed in an in-memory key-value store for retrieval. #### HOW TO RUN THE NEW BENCHMARK To install and run the rebatch benchmark, use the following commands: ``` ./benchpress_cli.py -b ai install chm_a // Install the chm workload representing workload A ./benchpress_cli.py -b ai install chm_b // Install the chm workload representing workload B ./benchpress_cli.py -b ai run chm_a // Run the chm workload representing workload A ./benchpress_cli.py -b ai run chm_b // Run the chm workload representing workload B ``` #### FILES ADDED AND MODIFIED ``` - benchpress - configs - benchmarks_ai.yml // Added the new chm benchmark. - jobs_ai.yml // Added two new chm benchmark jobs. - plugins - parsers.py - chm.py // Added a new parser for the chm benchmark. - __init__.py // Registered the new parser. - packages - chm - install_chm.sh // Added a new installation script for chm benchmark. - cleanup_chm.sh // Added a new cleanup script for chm benchmark. - ChmBenchmark.cpp // Added a benchmark simuates the concurrent hash map workload. - CMakeLists.txt // CMake file to compile the benchmark. - ConcurrentHashMap.h // A sharded concurrent hash map implementation - model_a.dist // Key distribution file for workload A. - model_b.dist // Key distribution file for workload B. - BUCK // Updated to include the new benchmark components. ... ``` Differential Revision: D77214563
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…f. (facebookresearch#147) Summary: Pull Request resolved: facebookresearch#147 This update introduces a new benchmark type, CHM, to the AI benchmark suite. The CHM benchmark simulates the usage pattern of a concurrent hash map in machine learning workloads, where certain key-value pairs are hashed in an in-memory key-value store for retrieval. #### HOW TO RUN THE NEW BENCHMARK To install and run the rebatch benchmark, use the following commands: ``` ./benchpress_cli.py -b ai install chm_a // Install the chm workload representing workload A ./benchpress_cli.py -b ai install chm_b // Install the chm workload representing workload B ./benchpress_cli.py -b ai run chm_a // Run the chm workload representing workload A ./benchpress_cli.py -b ai run chm_b // Run the chm workload representing workload B ``` #### FILES ADDED AND MODIFIED ``` - benchpress - configs - benchmarks_ai.yml // Added the new chm benchmark. - jobs_ai.yml // Added two new chm benchmark jobs. - plugins - parsers.py - chm.py // Added a new parser for the chm benchmark. - __init__.py // Registered the new parser. - packages - chm - install_chm.sh // Added a new installation script for chm benchmark. - cleanup_chm.sh // Added a new cleanup script for chm benchmark. - ChmBenchmark.cpp // Added a benchmark simuates the concurrent hash map workload. - CMakeLists.txt // CMake file to compile the benchmark. - ConcurrentHashMap.h // A sharded concurrent hash map implementation - model_a.dist // Key distribution file for workload A. - model_b.dist // Key distribution file for workload B. - BUCK // Updated to include the new benchmark components. ... ``` Differential Revision: D77214563
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…f. (facebookresearch#147) Summary: This update introduces a new benchmark type, CHM, to the AI benchmark suite. The CHM benchmark simulates the usage pattern of a concurrent hash map in machine learning workloads, where certain key-value pairs are hashed in an in-memory key-value store for retrieval. #### HOW TO RUN THE NEW BENCHMARK To install and run the rebatch benchmark, use the following commands: ``` ./benchpress_cli.py -b ai install chm_a // Install the chm workload representing workload A ./benchpress_cli.py -b ai install chm_b // Install the chm workload representing workload B ./benchpress_cli.py -b ai run chm_a // Run the chm workload representing workload A ./benchpress_cli.py -b ai run chm_b // Run the chm workload representing workload B ``` #### FILES ADDED AND MODIFIED ``` - benchpress - configs - benchmarks_ai.yml // Added the new chm benchmark. - jobs_ai.yml // Added two new chm benchmark jobs. - plugins - parsers.py - chm.py // Added a new parser for the chm benchmark. - __init__.py // Registered the new parser. - packages - chm - install_chm.sh // Added a new installation script for chm benchmark. - cleanup_chm.sh // Added a new cleanup script for chm benchmark. - ChmBenchmark.cpp // Added a benchmark simuates the concurrent hash map workload. - CMakeLists.txt // CMake file to compile the benchmark. - ConcurrentHashMap.h // A sharded concurrent hash map implementation - model_a.dist // Key distribution file for workload A. - model_b.dist // Key distribution file for workload B. - BUCK // Updated to include the new benchmark components. ... ``` Differential Revision: D77214563
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…f. (facebookresearch#147) Summary: Pull Request resolved: facebookresearch#147 This update introduces a new benchmark type, CHM, to the AI benchmark suite. The CHM benchmark simulates the usage pattern of a concurrent hash map in machine learning workloads, where certain key-value pairs are hashed in an in-memory key-value store for retrieval. #### HOW TO RUN THE NEW BENCHMARK To install and run the rebatch benchmark, use the following commands: ``` ./benchpress_cli.py -b ai install chm_a // Install the chm workload representing workload A ./benchpress_cli.py -b ai install chm_b // Install the chm workload representing workload B ./benchpress_cli.py -b ai run chm_a // Run the chm workload representing workload A ./benchpress_cli.py -b ai run chm_b // Run the chm workload representing workload B ``` #### FILES ADDED AND MODIFIED ``` - benchpress - configs - benchmarks_ai.yml // Added the new chm benchmark. - jobs_ai.yml // Added two new chm benchmark jobs. - plugins - parsers.py - chm.py // Added a new parser for the chm benchmark. - __init__.py // Registered the new parser. - packages - chm - install_chm.sh // Added a new installation script for chm benchmark. - cleanup_chm.sh // Added a new cleanup script for chm benchmark. - ChmBenchmark.cpp // Added a benchmark simuates the concurrent hash map workload. - CMakeLists.txt // CMake file to compile the benchmark. - ConcurrentHashMap.h // A sharded concurrent hash map implementation - model_a.dist // Key distribution file for workload A. - model_b.dist // Key distribution file for workload B. - BUCK // Updated to include the new benchmark components. ... ``` Differential Revision: D77214563
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…f. (#147) Summary: Pull Request resolved: #147 This update introduces a new benchmark type, CHM, to the AI benchmark suite. The CHM benchmark simulates the usage pattern of a concurrent hash map in the critical machine learning workloads, where certain key-value pairs are cached in an in-memory key-value concurrent hashmap for retrieval. #### HOW TO RUN THE NEW BENCHMARK To install and run the rebatch benchmark, use the following commands: ``` ./benchpress_cli.py -b ai install chm_a // Install the chm workload representing workload A ./benchpress_cli.py -b ai install chm_b // Install the chm workload representing workload B ./benchpress_cli.py -b ai run chm_a // Run the chm workload representing workload A ./benchpress_cli.py -b ai run chm_b // Run the chm workload representing workload B ``` #### FILES ADDED AND MODIFIED ``` - benchpress - configs - benchmarks_ai.yml // Added the new chm benchmark. - jobs_ai.yml // Added two new chm benchmark jobs. - plugins - parsers.py - chm.py // Added a new parser for the chm benchmark. - __init__.py // Registered the new parser. - packages - chm - install_chm.sh // Added a new installation script for chm benchmark. - cleanup_chm.sh // Added a new cleanup script for chm benchmark. - ChmBenchmark.cpp // Added a benchmark simuates the concurrent hash map workload. - CMakeLists.txt // CMake file to compile the benchmark. - ConcurrentHashMap.h // A sharded concurrent hash map implementation - model_a.dist // Key distribution file for workload A. - model_b.dist // Key distribution file for workload B. - BUCK // Updated to include the new benchmark components. ... ``` Reviewed By: excelle08 Differential Revision: D77214563 fbshipit-source-id: 569b9b623bd3450920e99b004094bab00fd8d57d
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Summary:
This update introduces a new benchmark type, CHM, to the AI benchmark suite. The CHM benchmark simulates the usage pattern of a concurrent hash map in machine learning workloads, where certain key-value pairs are hashed in an in-memory key-value store for retrieval.
HOW TO RUN THE NEW BENCHMARK
To install and run the rebatch benchmark, use the following commands:
FILES ADDED AND MODIFIED
Differential Revision: D77214563