high performance computing on graphics processing units: hgpu.org

One of the fundamental issues in computer science is ordering a list of items. Although there is a huge number of sorting algorithms, sorting problem has attracted a great deal of research; because efficient sorting is important to optimize the use of other algorithms. Sorting algorithms have been studied extensively since past three decades. Their uses are found in many applications including real-time systems, operating systems, and discrete event simulations. In most cases, the efficiency of an application itself depends on usage of a sorting algorithm. Lately, the usage of graphic cards for general purpose computing has again revisited sorting algorithms. In this paper we extended our previous work regarding parallel sorting algorithms on GPU, and are presenting an analysis of parallel and sequential bitonic, odd-even and rank-sort algorithms on different GPU and CPU architectures. Their performance for various queue sizes is measured with respect to sorting time and rate and also the speed up of bitonic sort over odd-even sorting algorithms is shown on different GPUs and CPU. The algorithms have been written to exploit task parallelism model as available on multi-core GPUs using the OpenCL specification.