Design and Analysis of a 32-bit Embedded High-Performance Cluster Optimized for Energy and Performance
Design and Analysis of a 32-bit Embedded High-Performance Cluster Optimized for Energy and Performance
复制标题
针对能源和性能优化的 32 位嵌入式高性能集群的设计和分析
DOI：
10.1109/co-hpc.2014.7
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Vincent M. Weaver
中科院分区：
文献类型：
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作者：
Michael F. Cloutier;Chad Paradis;Vincent M. Weaver
越来越多的超级计算机正在使用低功耗嵌入式处理器，而不是传统的高性能内核。为了评估这种方法，我们研究了在运行HPL Linpack和STREAM基准测试时，在十个不同的32位ARM开发板上发现的能量和性能权衡。基于这些结果（以及其他实际问题），我们选择Raspberry Pi作为功耗感知嵌入式集群计算测试平台的基础。集群的每个节点都配备了功率测量电路，以便可以获得详细的集群范围内的功率测量，从而实现功率/性能协同设计实验。虽然我们的集群在性能上落后于最近的x86机器，但其强大的功能、可视化和散热特性使其成为教育和实验的优秀低成本平台。
A growing number of supercomputers are being built using processors with low-power embedded ancestry, rather than traditional high-performance cores. In order to evaluate this approach we investigate the energy and performance tradeoffs found with ten different 32-bit ARM development boards while running the HPL Linpack and STREAM benchmarks.Based on these results (and other practical concerns) we chose the Raspberry Pi as a basis for a power-aware embedded cluster computing testbed. Each node of the cluster is instrumented with power measurement circuitry so that detailed cluster-wide power measurements can be obtained, enabling power / performance co-design experiments.While our cluster lags recent x86 machines in performance, the power, visualization, and thermal features make it an excellent low-cost platform for education and experimentation.