260 research outputs found
The CBE Hardware Accelerator for Numerical Relativity: A Simple Approach
Hardware accelerators (such as the Cell Broadband Engine) have recently
received a significant amount of attention from the computational science
community because they can provide significant gains in the overall performance
of many numerical simulations at a low cost. However, such accelerators usually
employ a rather unfamiliar and specialized programming model that often
requires advanced knowledge of their hardware design. In this article, we
demonstrate an alternate and simpler approach towards managing the main
complexities in the programming of the Cell processor, called software caching.
We apply this technique to a numerical relativity application: a time-domain,
finite-difference Kerr black hole perturbation evolver, and present the
performance results. We obtain gains in the overall performance of generic
simulations that are close to the theoretical maximum that can be obtained
through our parallelization approach.Comment: 5 pages, 2 figures; Accepted for publication in the International
Journal of Modeling, Simulation, and Scientific Computing (IJMSSC
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
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
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