IATF: An Input-Aware Tuning Framework for Compact BLAS Based on ARMv8 CPUs

Author:

Wei Cunyang1,Jia Haipeng1,Zhang Yunquan1,Xu Liusha2,Qi Ji2

Affiliation:

1. The Institute of Computing Technology of the Chinese Academy of Sciences, China

2. Huawei Technologies Co., Ltd., China

Publisher

ACM

Reference23 articles.

1. [n.d.]. ARM PERFORMANCE LIBRARIES. https://developer.arm.com/tools-and-software/server-and-hpc/compile/arm-compiler-for-linux/arm-performance-libraries [n.d.]. ARM PERFORMANCE LIBRARIES. https://developer.arm.com/tools-and-software/server-and-hpc/compile/arm-compiler-for-linux/arm-performance-libraries

2. [n.d.]. Intel oneAPI Math Kernel Library. https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl.html [n.d.]. Intel oneAPI Math Kernel Library. https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl.html

3. [n.d.]. OpenBLAS:An optimized BLAS library. http://www.openblas.net/ [n.d.]. OpenBLAS:An optimized BLAS library. http://www.openblas.net/

4. Performance, Design, and Autotuning of Batched GEMM for GPUs

5. Demystifying Parallel and Distributed Deep Learning

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5. LBBGEMM: A Load-balanced Batch GEMM Framework on ARM CPU s;2022 IEEE 24th Int Conf on High Performance Computing & Communications; 8th Int Conf on Data Science & Systems; 20th Int Conf on Smart City; 8th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys);2022-12

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