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Exploring the Potential of GPU-initiated Communications in HPC Applications
DescriptionThe two-sided MPI has become a de facto standard for communication on a distributed memory system. As high-performance GPU computing becomes the trend, some numerical methods have a relatively simple communication pattern adhering to the BSP model find MPI and its CUDA-aware variant can satisfy the performance requirements. Conversely, DAG-like computations have a more complex communication pattern and find it hard to scale to multiple GPUs. Thus, GPU-initiated one-sided communication becomes a viable solution for multi-GPU scaling. However, the lack of deep understanding of GPU-initiated one-sided communication and the real impact on applications performance become a hurdle. In this work, we use a multi-GPU SpTRSV, which is used in conjunction with Sparse LU for solving sparse linear systems, either as a direct solver or as a precondition, to demonstrate our multi-GPU SpTRSV implementation using NVSHMEM achieves up to 3x speedup on Perlmutter compared to a single GPU implementation.
Author/Presenter
Event Type
Workshop
TimeMonday, 13 November 20232:21pm - 2:24pm MST
Location505
State of the Practice
W