Introducing MareNostrum5: A European pre-exascale energy-efficient system designed to serve a broad spectrum of scientific workloads

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 : 2025-09-10 DOI:10.1016/j.future.2025.108125

Fabio Banchelli , Marta Garcia-Gasulla , Filippo Mantovani , Joan Vinyals , Josep Pocurull , David Vicente , Beatriz Eguzkitza , Flavio C.C. Galeazzo , Mario C. Acosta , Sergi Girona

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Abstract

MareNostrum5 is a pre-exascale supercomputer at the Barcelona Supercomputing Center (BSC), part of the EuroHPC Joint Undertaking. With a peak performance of 314 petaflops, MareNostrum5 features a hybrid architecture comprising Intel Sapphire Rapids CPUs, NVIDIA Hopper GPUs, and DDR5 and high-bandwidth memory (HBM), organized into four partitions optimized for diverse workloads. This document evaluates MareNostrum5 through micro-benchmarks (floating-point performance, memory bandwidth, interconnect throughput), HPC benchmarks (HPL and HPCG), and application studies using Alya, OpenFOAM, and IFS. It highlights MareNostrum5’s scalability, efficiency, and energy performance, utilizing the EAR (Energy Aware Runtime) framework to assess power consumption and the effects of direct liquid cooling. Additionally, HBM and DDR5 configurations are compared to examine memory performance trade-offs. Designed to complement standard technical documentation, this study provides insights to guide both new and experienced users in optimizing their workloads and maximizing MareNostrum5’s computational capabilities.

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介绍MareNostrum5：欧洲前百亿亿次节能系统，旨在服务于广泛的科学工作负载

MareNostrum5是巴塞罗那超级计算中心（BSC）的一台前百亿亿次超级计算机，是欧洲高性能计算联合项目的一部分。MareNostrum5的峰值性能为每秒314千万亿次，采用混合架构，包括英特尔Sapphire Rapids cpu、NVIDIA Hopper gpu、DDR5和高带宽内存（HBM），分为四个分区，针对不同的工作负载进行了优化。本文通过微基准测试（浮点性能、内存带宽、互连吞吐量）、HPC基准测试（HPL和HPCG）以及使用Alya、OpenFOAM和IFS的应用研究来评估MareNostrum5。它突出了MareNostrum5的可扩展性、效率和能源性能，利用EAR（能源感知运行时）框架来评估功耗和直接液体冷却的效果。此外，还比较了HBM和DDR5配置，以检查内存性能折衷。本研究旨在补充标准技术文档，为指导新用户和有经验的用户优化其工作负载和最大化MareNostrum5的计算能力提供了见解。

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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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.