Design and Analysis of a 32-bit Embedded High-Performance Cluster Optimized for Energy and Performance

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.