Researchers at the Georgia Tech Research Institute (GTRI) and the Georgia Tech School of Electrical and Computer Engineering are working on a project funded by the Air Force and DARPA to modify the Vector, Signal and Image Processing Library (VSIPL) to run on GPUs.
From the release at HPCwire
VSIPL is an open standard developed by embedded signal and image processing hardware and software vendors, academia, application developers and government labs. GPU VSIPL is available for download at http://gpu-vsipl.gtri.gatech.edu/.
The researchers are currently writing the functions in Nvidia’s CUDA language, but the underlying principles can be applied to GPUs developed by other companies, according to Campbell. With GPU VSIPL, engineers can use high-level functions in their C programs to perform linear algebra and signal processing operations, and recompile with GPU VSIPL to take advantage of the speed of the GPU. Studies have shown that VSIPL functions operate between 20 and 350 times faster on a GPU than a central processing unit, depending on the function