Friday, May 29, 2009
In Proceedings of the 23rd IEEE International Parallel and Distributed Processing Symposium (IPDPS), May 2009
The availability of easily programmable manycore CPUs and GPUs has motivated investigations into how to best exploit their tremendous computational power for scientific computing. Here we demonstrate how a systems biology application—detection and tracking of white blood cells in video microscopy—can be accelerated by 200x using a CUDA-capable GPU. Because the algorithms and implementation challenges are common to a wide range of applications, we discuss general techniques that allow programmers to make efficient use of a manycore GPU.