Intel(R) SHMEM: GPU-initiated OpenSHMEM using SYCL
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | , , , , , |
|---|---|
| Format: | Preprint |
| Publié: |
2024
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| _version_ | 1866913523729170432 |
|---|---|
| author | Brooks, Alex Marshall, Philip Ozog, David Rahman, Md. Wasi-ur- Stewart, Lawrence Tom, Rithwik |
| author_facet | Brooks, Alex Marshall, Philip Ozog, David Rahman, Md. Wasi-ur- Stewart, Lawrence Tom, Rithwik |
| contents | Modern high-end systems are increasingly becoming heterogeneous, providing users options to use general purpose Graphics Processing Units (GPU) and other accelerators for additional performance. High Performance Computing (HPC) and Artificial Intelligence (AI) applications are often carefully arranged to overlap communications and computation for increased efficiency on such platforms. This has led to efforts to extend popular communication libraries to support GPU awareness and more recently, GPU-initiated operations. In this paper, we present Intel SHMEM, a library that enables users to write programs that are GPU aware, in that API calls support GPU memory, and also support GPU-initiated communication operations by embedding OpenSHMEM style calls within GPU kernels. We also propose thread-collaborative extensions to the OpenSHMEM standard that can enable users to better exploit the strengths of GPUs. Our implementation adapts to choose between direct load/store from GPU and the GPU copy engine based transfer to optimize performance on different configurations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_20476 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Intel(R) SHMEM: GPU-initiated OpenSHMEM using SYCL Brooks, Alex Marshall, Philip Ozog, David Rahman, Md. Wasi-ur- Stewart, Lawrence Tom, Rithwik Distributed, Parallel, and Cluster Computing Modern high-end systems are increasingly becoming heterogeneous, providing users options to use general purpose Graphics Processing Units (GPU) and other accelerators for additional performance. High Performance Computing (HPC) and Artificial Intelligence (AI) applications are often carefully arranged to overlap communications and computation for increased efficiency on such platforms. This has led to efforts to extend popular communication libraries to support GPU awareness and more recently, GPU-initiated operations. In this paper, we present Intel SHMEM, a library that enables users to write programs that are GPU aware, in that API calls support GPU memory, and also support GPU-initiated communication operations by embedding OpenSHMEM style calls within GPU kernels. We also propose thread-collaborative extensions to the OpenSHMEM standard that can enable users to better exploit the strengths of GPUs. Our implementation adapts to choose between direct load/store from GPU and the GPU copy engine based transfer to optimize performance on different configurations. |
| title | Intel(R) SHMEM: GPU-initiated OpenSHMEM using SYCL |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2409.20476 |