高性能计算应用的泄漏能量估算

Aditya M. Deshpande, J. Draper
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引用次数: 6

摘要

大规模高性能系统是能量受限的。这些机器拥有数千个处理核心,包含大量的片内缓存。随着晶体管阈值的不断降低,漏电流和能量损失急剧增加。结合这两种趋势,片上缓存负责总泄漏能量损失的很大一部分。在这项工作中,我们在广泛的应用中量化了片上泄漏能量损失。我们的方案配置应用程序来测量缓存访问,以便估计不同级别缓存的能耗。我们的研究表明,泄漏能量是片上缓存能量耗散的主要形式,可能占到总缓存能量的80%,并且随着每一代新半导体工艺的发展,这一趋势有望增加。我们的结果还表明,编译器优化对缓存的总能耗的影响非常有限,并且无论编译器优化如何,缓存中的泄漏问题都不能通过软件技术有效地解决,而需要在电路和体系结构级别进行干预。在攻击构建百亿亿级系统的能量障碍时,缓存中的泄漏问题不容忽视。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Leakage energy estimates for HPC applications
Large-scale high-performance systems are energy constrained. With thousands of processing cores at their disposal, these machines contain large amounts of on-chip caches. With a trend of decreasing thresholds in transistors, the amount of leakage current and energy losses has increased dramatically. Coupling the two trends, on-chip caches are responsible for a large portion of total leakage energy losses. In this work, we quantify the on-chip leakage energy losses across a wide set of applications. Our scheme profiles applications to measure cache accesses in order to estimate energy consumption across various levels of caches. Our study indicates that the leakage energy is the dominant form of energy dissipation in on-chip caches and may account for up to 80% of total cache energy, and this trend is expected to increase with every new generation of semiconductor process. Our results also suggest that compiler optimizations have a very limited effect on the total energy consumption of the caches and irrespective of the compiler optimizations, the problem of leakage in caches cannot be effectively addressed by software techniques but requires intervention at circuit and architectural levels. The problem of leakage in caches cannot be neglected in attacking the energy barrier to building exascale systems.
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