GPA: A GPU Performance Advisor Based on Instruction Sampling

Developing efficient GPU kernels can be difficult because of the complexity of GPU architectures and programming models. Existing performance tools only provide coarse-grained tuning advice at the kernel level, if any. In this paper, we describe GPA, a performance advisor for NVIDIA GPUs that sugges...

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Bibliographic Details

Published in:	2021 IEEE/ACM International Symposium on Code Generation and Optimization (CGO) pp. 115 - 125
Main Authors:	Zhou, Keren, Meng, Xiaozhu, Sai, Ryuichi, Mellor-Crummey, John
Format:	Conference Proceeding
Language:	English
Published:	IEEE 27.02.2021
Subjects:	Computer architecture Graphics processing units High performance computing Kernel Optimization Parallel architectures Parallel programming Performance analysis Programming Tuning
Online Access:	Get full text
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