Embracing Irregular Parallelism in HPC with YGM

YGM is a general-purpose asynchronous distributed computing library for C++/MPI, designed to handle the irregular data access patterns and small messages of graph algorithms and data science applications. It uses data serialization to give an easily usable active message interface and message aggreg...

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Vydáno v:International Conference for High Performance Computing, Networking, Storage and Analysis (Online) s. 1 - 13
Hlavní autoři: Steil, Trevor, Reza, Tahsin, Priest, Benjamin W., Pearce, Roger
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: ACM 11.11.2023
Témata:
asynchronous communication
Benchmark testing
Costs
distributed computing
Programming
Random access memory
Scalability
Social networking (online)
Throughput
ISSN:2167-4337
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Popis
Shrnutí:YGM is a general-purpose asynchronous distributed computing library for C++/MPI, designed to handle the irregular data access patterns and small messages of graph algorithms and data science applications. It uses data serialization to give an easily usable active message interface and message aggregation to maximize application throughput. Our design philosophy makes a tradeoff that increases network bandwidth utilization at the cost of added latency. We provide a suite of benchmarks showcasing YGM's performance. Compared to similar distributed active message benchmark implementations that do not provide message buffering, we are able to achieve over 10x throughput on thousands of cores at a latency cost that can be as small as 2x or as large as 100x, depending on the machine being used. For applications that can be written to be latency-tolerant, this represents a significant potential performance improvement through using YGM.
ISSN:2167-4337
DOI:10.1145/3581784.3607103