  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.
