Understanding the GPU Microarchitecture to Achieve Bare-Metal Performance Tuning

Author:

Zhang Xiuxia1,Tan Guangming1,Xue Shuangbai1,Li Jiajia2,Zhou Keren1,Chen Mingyu1

Affiliation:

1. Chinese Academy of Sciences, Beijing, China

2. Georgia Institute of Technology, Atlanta, GA, USA

Funder

the National Key Research and Development Program of China

National Natural Science Foundation of China

the joint deep learning lab of Institute of Computing Technology and Sugon and CAS Holdings

National 863 Foundation of China

Publisher

ACM

Reference34 articles.

1. Envytools. https://github.com/envytools/envytools. Envytools. https://github.com/envytools/envytools.

2. AMD. clMath. https://github.com/clMathLibraries. AMD. clMath. https://github.com/clMathLibraries.

3. Extending the ArchC Language for Automatic Generation of Assemblers

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