性能和效率：在带宽受限的高性能计算应用程序上的现代处理器的多代基准

IF 6.2 2区计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS

Future Generation Computer Systems-The International Journal of Escience Pub Date : 2025-03-06 DOI:10.1016/j.future.2025.107793

Balázs Drávai, István Z. Reguly

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引用次数: 0

摘要

在过去的两年里，为了满足市场需求，推出了许多新的x86处理器。英特尔推出了四个系列的至强处理器，具有一些新颖的架构特征；首先是蓝宝石Rapids一代，其特点是采用了内置HBM的版本，然后是Emerald Rapids一代，随后又推出了以性能为导向的Granite Rapids和以效率为导向的Sierra Forest系列。在这项工作中，我们评估了英特尔和AMD cpu的不同一代和变体的cpu的性能和能效，特别关注带宽受限的高性能计算（HPC）应用。我们对比运行时间和能源消耗数据，并跟踪几代人之间的趋势。我们进一步研究了启用位置改进优化如何提高缓存重用和整体性能，同时减少能源使用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Performance and efficiency: A multi-generational benchmark of modern processors on bandwidth-bound HPC applications

The last two years has seen the launch of a multitude of new x86 processors, in reaction to market demand. Intel has launched four families of Xeon Processors, with some novel architectural features; first the Sapphire Rapids generation which featured a version with on-package HBM, the Emerald Rapids generation, and then differentiated by releasing the performance-oriented Granite Rapids and the efficiency-oriented Sierra Forest families. In this work, we evaluate the performance and energy efficiency of CPUs from each of different generations and variants of Intel and AMD CPUs, with a particular focus on bandwidth-bound high performance computing (HPC) applications. We contrast runtime and energy consumption figures and track trends across generations. We furthermore study how enabling locality-improving optimizations increases cache reuse and overall performance, while reducing energy use.

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来源期刊

Future Generation Computer Systems-The International Journal of Escience 工程技术-计算机：理论方法

CiteScore

19.90

自引率

2.70%

发文量

376

审稿时长

10.6 months

期刊介绍： Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications. Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration. Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.