Simplifying low-level GPU programming with GAS

Da Yan, Wei Wang, Xiaowen CHU

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

Abstract

Many low-level optimizations for NVIDIA GPU can only be implemented in native hardware assembly (SASS). However, programming in SASS is unproductive and not portable. To simplify low-level GPU programming, we present GAS (Gpu ASsembly), a PTX-like language that provides a stable instruction set across hardware architectures while giving programmers a low-level control of code execution. We demonstrate that GAS can be used with ease for low-level benchmarking and performance tuning in the context of Tensor Core HGEMM.

Original languageEnglish
Title of host publicationPPoPP 2021 - Proceedings of the 2021 26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming
PublisherAssociation for Computing Machinery
Pages469-471
Number of pages3
ISBN (Electronic)9781450382946
DOIs
Publication statusPublished - 17 Feb 2021
Event26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP 2021 - Virtual, Online, Korea, Republic of
Duration: 27 Feb 20213 Mar 2021

Publication series

NameProceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP

Conference

Conference26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP 2021
Country/TerritoryKorea, Republic of
CityVirtual, Online
Period27/02/213/03/21

Scopus Subject Areas

  • Software

User-Defined Keywords

  • compiler
  • GPU
  • SASS

Fingerprint

Dive into the research topics of 'Simplifying low-level GPU programming with GAS'. Together they form a unique fingerprint.

Cite this