在新兴多核超级计算机上扩展全到全操作
Scaling All-to-all Operations Across Emerging Many-Core Supercomputers
AI总结：
本文提出新型算法提升新兴多核超级计算机上全到全操作性能，实现3倍速度提升。
摘要：
在MPI中实现高效的全到全集体操作对于快速傅里叶变换、转置和机器学习应用至关重要。现有的许多实现用于新兴系统的全到全交换，所取得的性能取决于许多因素，包括消息大小、进程数量、架构和并行系统分区。本文提出了针对新兴多核系统的新型全到全算法。此外，本文还对现有算法和系统MPI进行了性能分析，新型算法在32个最先进的Sapphire Rapids系统节点上比系统MPI快了3倍。
英文摘要：
Performant all-to-all collective operations in MPI are critical to fast Fourier transforms, transposition, and machine learning applications. There are many existing implementations for all-to-all exchanges on emerging systems, with the achieved performance dependent on many factors, including message size, process count, architecture, and parallel system partition. This paper presents novel all-to-all algorithms for emerging many-core systems. Further, the paper presents a performance analysis against existing algorithms and system MPI, with novel algorithms achieving up to 3x speedup over system MPI at 32 nodes of state-of-the-art Sapphire Rapids systems.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
