ck-rpi-optimization-results:通过可移植的软件包管理器通过可定制的Collective Knowled...
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ck-rpi-optimization-results:通过可移植的软件包管理器通过可定制的Collective Knowledge工作流框架，在RPi3上演示了编译器自动调整，人群调整和机器学习。 这项技术在速度，准确性，能源和成本方面支持帕累托高效的软件-硬件深度学习竞赛 （2000个子文件） 
rpi3-autotuning-susan-gcc4-interactive.html 768KB rpi3-autotuning-zlib-decode-gcc4-interactive.html 510KB rpi3-autotuning-susan-gcc7-interactive.html 506KB rpi3-autotuning-zlib-encode-gcc7-interactive.html 441KB rpi3-autotuning-zlib-encode-gcc7-reactions-interactive.html 432KB interactive.html 429KB rpi3-autotuning-zlib-decode-gcc7-interactive.html 404KB rpi3-autotuning-zlib-decode-gcc7-reactions-interactive.html 401KB rpi3-autotuning-zlib-encode-gcc4-reactions-interactive.html 369KB rpi3-autotuning-zlib-decode-gcc4-reactions-interactive.html 363KB rpi3-autotuning-zlib-encode-gcc4-interactive.html 352KB ck-rpi-crowdtuning-report.html 243KB 74089e922ca45f99-table.html 16KB 74089e922ca45f99-table.html 16KB 74089e922ca45f99-table.html 16KB save_all_model_data_tmp_table.html 16KB save_all_model_data_tmp_table_full.html 16KB 1ea731443e29f6ce-table.html 11KB 1ea731443e29f6ce-table.html 11KB 1ea731443e29f6ce-table.html 11KB 142fbaf8c4fb48b8-table.html 7KB save_all_model_data_tmp_table_short.html 7KB 9e4b1594d3b99443-table2.html 5KB 4373f49dea7663db-table3.html 4KB 4373f49dea7663db-table3.html 4KB 4373f49dea7663db-table3.html 4KB 9e4b1594d3b99443-table1.html 4KB 9e4b1594d3b99443-table1.html 4KB 9e4b1594d3b99443-table1.html 4KB 4373f49dea7663db-table1.html 4KB 4373f49dea7663db-table1.html 4KB 4373f49dea7663db-table1.html 4KB 2318dcb514171ad4-table1.html 3KB 2318dcb514171ad4-table1.html 3KB 2318dcb514171ad4-table1.html 3KB 3f15a01f17d48b7b-table1.html 3KB 3f15a01f17d48b7b-table1.html 3KB 3f15a01f17d48b7b-table1.html 3KB 6fa4e9181faa1385.solutions.html 3KB 6fa4e9181faa1385.solutions.html 3KB 6fa4e9181faa1385.solutions.html 3KB 22f5af13e8e498aa-table1.html 3KB 22f5af13e8e498aa-table1.html 3KB 22f5af13e8e498aa-table1.html 3KB 269da4a48ecdfe46-table1.html 3KB 269da4a48ecdfe46-table1.html 3KB 269da4a48ecdfe46-table1.html 3KB 74ba8b07475626f5-table1.html 2KB 74ba8b07475626f5-table1.html 2KB 74ba8b07475626f5-table1.html 2KB 4373f49dea7663db-table2.html 2KB 4373f49dea7663db-table2.html 2KB 4373f49dea7663db-table2.html 2KB bae9e4979bd3bc4b-table1.html 2KB bae9e4979bd3bc4b-table1.html 2KB bae9e4979bd3bc4b-table1.html 2KB 41ed88477436dd3e.solutions.html 2KB 41ed88477436dd3e.solutions.html 2KB 41ed88477436dd3e.solutions.html 2KB 749a8998a2e29db5-table1.html 2KB 749a8998a2e29db5-table1.html 2KB 749a8998a2e29db5-table1.html 2KB 8d7b4b7a7b8545e7-table1.html 1KB 8d7b4b7a7b8545e7-table1.html 1KB 8d7b4b7a7b8545e7-table1.html 1KB 08ac094d04acd157-table.html 371B 08ac094d04acd157-table.html 371B 08ac094d04acd157-table.html 371B save_all_model_data_tmp_table_milepost.html 371B
process_model_using_nearest_neighbour_ft57_ft65_tmp.GCC_4.9.2.normalized.json 3.49MB process_model_using_nearest_neighbour_ft57_ft65_tmp.GCC_7.1.0.normalized.json 3.47MB prepare_reactions_model_train_reduced_result.GCC_4.9.2.json 3.47MB prepare_reactions_model_train_reduced_result.GCC_7.1.0.json 3.47MB process_model_using_nearest_neighbour_ft1_ft56_tmp.GCC_4.9.2.normalized.json 3.46MB process_model_using_nearest_neighbour_ft1_ft65_tmp.GCC_4.9.2.normalized.json 3.45MB process_model_using_nearest_neighbour_ft1_ft56_tmp.GCC_7.1.0.normalized.json 3.44MB process_model_using_nearest_neighbour_ft1_ft65_tmp.GCC_7.1.0.normalized.json 3.43MB process_model_using_nearest_neighbour_ft66_ft121_tmp.GCC_4.9.2.json 3.43MB prepare_reactions_model_train_reduced_result.GCC_4.9.2.json 3.42MB process_model_using_nearest_neighbour_ft66_ft121_tmp.GCC_4.9.2.normalized.json 3.42MB process_model_using_nearest_neighbour_ft57_ft121_tmp.GCC_4.9.2.normalized.json 3.42MB prepare_reactions_model_train_ref_result.GCC_4.9.2.json 3.41MB process_model_using_nearest_neighbour_ft1_ft121_tmp.GCC_4.9.2.normalized.json 3.41MB process_model_using_nearest_neighbour_ft66_ft121_tmp.GCC_7.1.0.json 3.41MB prepare_reactions_model_train_reduced_result.GCC_7.1.0.json 3.4MB process_model_using_nearest_neighbour_ft66_ft121_tmp.GCC_7.1.0.normalized.json 3.4MB process_model_using_nearest_neighbour_ft57_ft121_tmp.GCC_7.1.0.normalized.json 3.4MB prepare_reactions_model_train_ref_result.GCC_7.1.0.json 3.39MB process_model_using_nearest_neighbour_ft1_ft121_tmp.GCC_7.1.0.normalized.json 3.39MB process_model_using_nearest_neighbour_ft1_ft56_tmp.GCC_4.9.2.json 3.39MB process_model_using_nearest_neighbour_ft1_ft121_tmp.GCC_4.9.2.json 3.39MB process_model_using_nearest_neighbour_ft57_ft121_tmp.GCC_4.9.2.json 3.38MB process_model_using_nearest_neighbour_ft1_ft65_tmp.GCC_4.9.2.json 3.38MB process_model_using_nearest_neighbour_ft57_ft65_tmp.GCC_4.9.2.json 3.38MB process_model_using_nearest_neighbour_ft1_ft56_tmp.GCC_7.1.0.json 3.37MB process_model_using_nearest_neighbour_ft1_ft121_tmp.GCC_7.1.0.json 3.37MB process_model_using_nearest_neighbour_ft57_ft121_tmp.GCC_7.1.0.json 3.37MB process_model_using_nearest_neighbour_ft1_ft65_tmp.GCC_7.1.0.json 3.37MB process_model_using_nearest_neighbour_ft57_ft65_tmp.GCC_7.1.0.json 3.37MB prepare_reactions_model_train_ref_result.GCC_4.9.2.json 2.13MB共 2000 条
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