  We present an implementation of the overlap-and-save method, a method for the
convolution of very long signals with short response functions, which is
tailored to GPUs. We have implemented several FFT algorithms (using the CUDA
programming language) which exploit GPU shared memory, allowing for GPU
accelerated convolution. We compare our implementation with an implementation
of the overlap-and-save algorithm utilizing the NVIDIA FFT library (cuFFT). We
demonstrate that by using a shared memory based FFT we can achieved significant
speed-ups for certain problem sizes and lower the memory requirements of the
overlap-and-save method on GPUs.
