A More Scalable Sparse Dynamic Data Exchange
Andrew Geyko, Gerald Collom, Derek Schafer, Patrick G. Bridges, Amanda Bienz · 2024
Parallel architectures are continually increasing in performance and scale while underlying algorithmic infrastruc-ture often fails 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 is 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 applications to utilize the variety of provided optimizations for sparse dynamic data exchange methods. Fur-ther, the paper presents novel locality-aware sparse dynamic data exchange algorithms. Finally, performance results show locality-aware approaches achieve up to 128x over existing approaches when exchanging only pattern of communication, and up to 54x when exchanging data to be communicated as well.