Just-In-Time Execution Through On-Demand Resource Allocation in HPC Systems

A. Portero, M. Podhorányi, D. Hrbáč, Simone Libutti, G. Massari, W. Fornaciari
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引用次数: 0

Abstract

This article is centred on a mathematical weather forecasting model that must run regularly (i.e. 24/7) on an HPC system. Depending on the environmental conditions, each execution of the model may have a different deadline and a different accuracy requirement. In order to minimize power consumption and heat, we minimize resource allocation as far as the deadlines allow, thus evenly spreading resource usage over time while nonetheless complying with the deadlines. Our work relies on a run-time resource manager that adapts resource allocation to the runtime-variable performance demand of applications. The resource assignment is temperature-aware: the application is dynamically migrated on the coolest cores, and this has a positive impact on the system reliability.
在高性能计算系统中通过按需资源分配实现的实时执行
本文的中心是必须在高性能计算系统上定期(即24/7)运行的数学天气预报模型。根据环境条件的不同,模型的每次执行可能有不同的截止日期和不同的精度要求。为了最小化功耗和热量,我们在截止日期允许的范围内最小化资源分配,从而在遵守截止日期的同时均匀地分配资源使用。我们的工作依赖于一个运行时资源管理器,它根据应用程序的运行时可变性能需求调整资源分配。资源分配是温度敏感的:应用程序在最冷的核心上动态迁移,这对系统可靠性有积极的影响。
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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