Optimization Techniques for GPU Programming

Author:

Hijma Pieter1ORCID,Heldens Stijn2ORCID,Sclocco Alessio2ORCID,van Werkhoven Ben2ORCID,Bal Henri E.1ORCID

Affiliation:

1. Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

2. Netherlands eScience Center, Amsterdam, The Netherlands

Abstract

In the past decade, Graphics Processing Units have played an important role in the field of high-performance computing and they still advance new fields such as IoT, autonomous vehicles, and exascale computing. It is therefore important to understand how to extract performance from these processors, something that is not trivial. This survey discusses various optimization techniques found in 450 articles published in the last 14 years. We analyze the optimizations from different perspectives which shows that the various optimizations are highly interrelated, explaining the need for techniques such as auto-tuning.

Funder

Dutch Research Council

NWA-ORC Call

Netherlands eScience Center

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science,Theoretical Computer Science

Reference439 articles.

1. 2018. Frontier: OLCF’s Exascale Future. Retrieved July 2021 from https://www.olcf.ornl.gov/2018/02/13/frontier-olcfs-exascale-future/.

2. 2019. U.S. Department of Energy and Intel to Deliver First Exascale Supercomputer Argonne National Laboratory. Retrieved July 2021 from https://www.anl.gov/article/us-department-of-energy-and-intel-to-deliver-first-exascale-supercomputer.

3. 2020. May We Introduce: LUMI. Retrieved July 2021 from https://www.lumi-supercomputer.eu/may-we-introduce-lumi/.

4. On the development of variable size batched computation for heterogeneous parallel architectures;Abdelfattah A.;IEEE International Parallel and Distributed Processing Symposium Workshops,2016

5. Performance Tuning and Optimization Techniques of Fixed and Variable Size Batched Cholesky Factorization on GPUs

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