Exploring cross-layer power management for PGAS applications on the SCC platform
Proceedings of the 21st international symposium on High-Performance Parallel and Distributed Computing
A generic high-performance method for deinterleaving scientific data
Euro-Par'13 Proceedings of the 19th international conference on Parallel Processing
Sparse matrix-vector multiplication on the Single-Chip Cloud Computer many-core processor
Journal of Parallel and Distributed Computing
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Proceedings of Programming Models and Applications on Multicores and Manycores
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Over the past years there has been a steady change in CPU design towards both many-core processors and power-aware hardware architectures. These two trends are combined in the Intel Single-chip Cloud Computer (SCC), an experimental prototype with 48 Pentium cores created by Intel Labs. The SCC is a highly configurable many-core chip which provides unique opportunities to optimize run time, communication and memory access as well as power/energy consumption of parallel programs. The aim of this paper is to characterize the performance behavior of the chip with various power settings, mappings of processes/cores to memory controllers, etc through benchmarking. Analytical models are used to verify and interpret the results. Conclusions drawn from our benchmark outcomes are that data exchange based on message passing is faster than shared memory data exchange. Contrary to popular belief, lowest energy consumption is not achieved for the fastest execution time. Furthermore in order to improve the memory access behavior one should increase the clock frequency of both, mesh network and memory controllers. In general, the results of our investigations can be used to analyze the effect of power settings and architecture properties on the performance and energy consumption of parallel programs as well as assist in choosing appropriate settings for specific workloads.