高密度共享内存HPC节点能耗量化研究

Milos Puzovic, Srilatha Manne, Shay GalOn, M. Ono
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引用次数: 11

摘要

在本文中,我们介绍了一种新颖的,密集的,系统级片上多核联想NeXtScale系统®服务器,该服务器基于Cavium THUNDERX®ARMv8处理器,专为性能,能效和可编程性而设计。THUNDERX处理器被设计为在缓存一致的共享内存架构中扩展到96核。此外,该硬件系统具有电源接口板(PIB),可在NeXtScale™机箱中测量整个服务器板的高精度功耗。我们使用从PIB获得的数据来测量PARSEC和Splash-2基准测试的能耗,并演示如何使用来自THUNDERX处理器的可用硬件计数器来量化共享内存编程的不同方面(如缓存相干通信)所使用的能耗。我们表明,保持缓存一致性所需的能量可以忽略不计,并证明共享内存编程范式是未来节能高性能计算设计的可行候选。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantifying Energy Use in Dense Shared Memory HPC Node
In this paper we introduce a novel, dense, system-on-chip many-core Lenovo NeXtScale System® server based on the Cavium THUNDERX® ARMv8 processor that was designed for performance, energy efficiency and programmability. THUNDERX processor was designed to scale up to 96 cores in a cache coherent, shared memory architecture. Furthermore, this hardware system has a power interface board (PIB) that measures with high accuracy power draw across the server board in the NeXtScale™ chassis. We use data obtainable from PIB to measure the energy use of PARSEC and Splash-2 benchmarks and demonstrate how to use available hardware counters from THUNDERX processor in order to quantify the amount of energy that is used by different aspects of shared memory programming, such as cache coherent communication. We show that energy used required to keep caches coherent is negligible and demonstrate that shared memory programming paradigm is viable candidate for future energy aware HPC designs.
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