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Comparing Hardware Accelerators in Scientific Applications: A Case Study

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4 Author(s)
Weber, R. ; Dept. of Electr. Eng. & Comput. Sci., Univ. of Tennessee, Knoxville, TN, USA ; Gothandaraman, A. ; Hinde, R.J. ; Peterson, G.D.

Multicore processors and a variety of accelerators have allowed scientific applications to scale to larger problem sizes. We present a performance, design methodology, platform, and architectural comparison of several application accelerators executing a Quantum Monte Carlo application. We compare the application's performance and programmability on a variety of platforms including CUDA with Nvidia GPUs, Brook+ with ATI graphics accelerators, OpenCL running on both multicore and graphics processors, C++ running on multicore processors, and a VHDL implementation running on a Xilinx FPGA. We show that OpenCL provides application portability between multicore processors and GPUs, but may incur a performance cost. Furthermore, we illustrate that graphics accelerators can make simulations involving large numbers of particles feasible.

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Parallel and Distributed Systems, IEEE Transactions on  (Volume:22 ,  Issue: 1 )