An exploration of CUDA and CBEA for a gravitational wave data-analysis application (Einstein@Home)

We present a detailed approach for making use of two new computer hardware architectures -- CBEA and CUDA -- for accelerating a scientific data-analysis application (Einstein@Home). Our results suggest that both the architectures suit the application quite well and the achievable performance in the same software developmental time-frame, is nearly identical.Comment: Accepted for publication in International Conference on Parallel Processing and Applied Mathematics (PPAM 2009

High-Precision Numerical Simulations of Rotating Black Holes Accelerated by CUDA

Hardware accelerators (such as Nvidia's CUDA GPUs) have tremendous promise for computational science, because they can deliver large gains in performance at relatively low cost. In this work, we focus on the use of Nvidia's Tesla GPU for high-precision (double, quadruple and octal precision) numerical simulations in the area of black hole physics -- more specifically, solving a partial-differential-equation using finite-differencing. We describe our approach in detail and present the final performance results as compared with a single-core desktop processor and also the Cell BE. We obtain mixed results -- order-of-magnitude gains in overall performance in some cases and negligible gains in others.Comment: 6 pages, 1 figure, 1 table, Accepted for publication in the International Conference on High Performance Computing Systems (HPCS 2010