云平台上高性能计算的可扩展系统和软件架构

Risshab Srinivas Ramesh
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引用次数: 0

摘要

高性能计算(HPC)对于解决各领域的综合计算问题至关重要。随着高性能计算应用的规模和复杂性不断扩大,对可扩展系统和软件架构的需求变得至关重要。本文从硬件和软件两个方面全面概述了预置式高性能计算的体系结构,并详细介绍了构建预置式高性能计算集群所面临的相关挑战。它探讨了构建可扩展高性能计算系统和软件的设计原则、挑战和新兴趋势,解决了各种云平台上的并行性、内存层次结构、通信开销和容错等问题。通过综合研究成果和技术进步,本文旨在深入探讨可扩展的解决方案,以满足云计算上不断发展的高性能计算应用需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Scalable Systems and Software Architectures for High-Performance Computing on cloud platforms
High-performance computing (HPC) is essential for tackling complex computational problems across various domains. As the scale and complexity of HPC applications continue to grow, the need for scalable systems and software architectures becomes paramount. This paper provides a comprehensive overview of architecture for HPC on premise focusing on both hardware and software aspects and details the associated challenges in building the HPC cluster on premise. It explores design principles, challenges, and emerging trends in building scalable HPC systems and software, addressing issues such as parallelism, memory hierarchy, communication overhead, and fault tolerance on various cloud platforms. By synthesizing research findings and technological advancements, this paper aims to provide insights into scalable solutions for meeting the evolving demands of HPC applications on cloud.
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