@inproceedings{6257a7e50d40433da458badb4e54f5ba,
title = "shmem4py: High-Performance One-Sided Communication for Python Applications",
abstract = "This paper describes shmem4py, a Python wrapper for the OpenSHMEM application programming interface (API) which follows a design similar to that of the well-known mpi4py package. OpenSHMEM is a descendant of the one-sided communication library for the Cray T3D and it is known for its uncompromising performance for low-latency and high-throughput use cases involving one-sided and collective communication. OpenSHMEM is arguably one of the most efficient and portable abstractions for modern network architectures. Thanks to tight interoperability with NumPy, shmem4py provides a convenient parallel programming framework leveraging both the high-productivity NumPy feature set and the high-performance networking capabilities of OpenSHMEM. This paper discusses the design and performance characteristics of shmem4py in a variety of communication patterns relative to lower-level languages (C) as well as MPI and mpi4py.",
keywords = "High Performance Computing, MPI, OpenSHMEM, Python, shared memory",
author = "Marcin Rogowski and Hammond, {Jeff R.} and Keyes, {David E.} and Lisandro Dalcin",
note = "Publisher Copyright: {\textcopyright} 2023 Owner/Author.; 2023 International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023 ; Conference date: 12-11-2023 Through 17-11-2023",
year = "2023",
month = nov,
day = "12",
doi = "10.1145/3624062.3624602",
language = "English (US)",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "1185--1193",
booktitle = "Proceedings of 2023 SC Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023",
}