A More Scalable Sparse Dynamic Data Exchange
arxiv(2023)
摘要
Parallel architectures are continually increasing in performance and scale,
while underlying algorithmic infrastructure often fail to take full advantage
of available compute power. Within the context of MPI, irregular communication
patterns create bottlenecks in parallel applications. One common bottleneck is
the sparse dynamic data exchange, often required when forming communication
patterns within applications. There are a large variety of approaches for these
dynamic exchanges, with optimizations implemented directly in parallel
applications. This paper proposes a novel API within an MPI extension library,
allowing for applications to utilize the variety of provided optimizations for
sparse dynamic data exchange methods. Further, the paper presents novel
locality-aware sparse dynamic data exchange algorithms. Finally, performance
results show significant speedups up to 20x with the novel locality-aware
algorithms.
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