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 language | English |
|---|---|
| Title of host publication | PPoPP 2021 - Proceedings of the 2021 26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming |
| Publisher | Association for Computing Machinery |
| Pages | 469-471 |
| Number of pages | 3 |
| ISBN (Electronic) | 9781450382946 |
| DOIs | |
| Publication status | Published - 17 Feb 2021 |
| Event | 26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP 2021 - Virtual, Online, Korea, Republic of Duration: 27 Feb 2021 → 3 Mar 2021 |
Publication series
| Name | Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP |
|---|
Conference
| Conference | 26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP 2021 |
|---|---|
| Country/Territory | Korea, Republic of |
| City | Virtual, Online |
| Period | 27/02/21 → 3/03/21 |
Bibliographical note
Publisher Copyright:© 2021 Owner/Author.
Keywords
- GPU
- SASS
- compiler