  The latest Graphics Processing Units (GPUs) are reported to reach up to
  200 billion floating point operations per second (200 Gflops) and to have
price performance of 0.1 cents per M flop. These facts raise great interest in
the plausibility of extending the GPUs' use to non-graphics applications, in
particular numerical simulations on structured grids (lattice).
  We review previous work on using GPUs for non-graphics applications,
implement probability-based simulations on the GPU, namely the
  Ising and percolation models, implement vector operation benchmarks for the
GPU, and finally compare the CPU's and GPU's performance.
  A general conclusion from the results obtained is that moving computations
from the CPU to the GPU is feasible, yielding good time and price performance,
for certain lattice computations.
  Preliminary results also show that it is feasible to use them in parallel
