用于余热回收的 Frontier 超级计算机能源数据集。

IF 5.8 2区综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Scientific Data Pub Date : 2024-10-03 DOI:10.1038/s41597-024-03913-w

Jian Sun, Zhiming Gao, David Grant, Kashif Nawaz, Pengtao Wang, Cheng-Min Yang, Philip Boudreaux, Stephen Kowalski, Shean Huff

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引用次数: 0

摘要

惠普 Enterprise-Cray EX Frontier 是世界上第一台也是速度最快的超大规模超级计算机，位于美国田纳西州橡树岭领导计算设施。Frontier 耗电量很大，高达 8-30 兆瓦；这种巨大的能源需求会产生大量废热，需要采取大量冷却措施。尽管利用这些废热为校园供暖是橡树岭国家实验室（ORNL）的可持续发展目标，但 30 ℃-38 ℃ 的废热温度与标准 HVAC 系统存在兼容性问题。热泵系统在住宅环境和一些工业中非常普遍，可以有效地将低质量的热量提升为建筑物可用的能源。因此，以可再生电力为动力的热泵技术为大量回收废热提供了一个高效、经济的解决方案。然而，一个主要挑战是缺乏高性能计算（HPC）发热量和废热概况的基准数据。本文报告了 ORNL HPC 数据中心的电力需求和废热测量数据，旨在指导未来在大型数据中心（尤其是 HPC 级数据中心）优化废热回收的研究。

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Energy dataset of Frontier supercomputer for waste heat recovery.

The Hewlett Packard Enterprise-Cray EX Frontier is the world's first and fastest exascale supercomputer, hosted at the Oak Ridge Leadership Computing Facility in Tennessee, United States. Frontier is a significant electricity consumer, drawing 8-30 MW; this massive energy demand produces significant waste heat, requiring extensive cooling measures. Although harnessing this waste heat for campus heating is a sustainability goal at Oak Ridge National Laboratory (ORNL), the 30 °C-38 °C waste heat temperature poses compatibility issues with standard HVAC systems. Heat pump systems, prevalent in residential settings and some industries, can efficiently upgrade low-quality heat to usable energy for buildings. Thus, heat pump technology powered by renewable electricity offers an efficient, cost-effective solution for substantial waste heat recovery. However, a major challenge is the absence of benchmark data on high-performance computing (HPC) heat generation and waste heat profiles. This paper reports power demand and waste heat measurements from an ORNL HPC data centre, aiming to guide future research on optimizing waste heat recovery in large-scale data centres, especially those of HPC calibre.

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来源期刊

Scientific Data Social Sciences-Education

CiteScore

11.20

自引率

4.10%

发文量

689

审稿时长

16 weeks

期刊介绍： Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.