  Modern graphics hardware is designed for highly parallel numerical tasks and
provides significant cost and performance benefits. Graphics hardware vendors
are now making available development tools to support general purpose high
performance computing. Nvidia's CUDA platform, in particular, offers direct
access to graphics hardware through a programming language similar to C. Using
the CUDA platform we have implemented a Wilson-Dirac operator which runs at an
effective 68 Gflops on the Tesla C870. The recently released GeForce GTX 280
runs this same code at 92 Gflops, and we expect further improvement pending
code optimization.
