Fast, Scalable Parallel Comparison Sort on Hybrid Multicore Architectures

Sorting has been a topic of immense research value since the inception of Computer Science. Hybrid computing on multicore architectures involves computing simultaneously on a tightly coupled heterogeneous collection of devices. In this work, we consider a multicore CPU along with a many core GPU as our experimental hybrid platform. In this work, we present a hybrid comparison based sorting algorithm which utilizes a many-core GPU and a multi-core CPU to perform sorting. The algorithm is broadly based on splitting the input list according to a large number of splitters followed by creating independent sub lists. Sorting the independent sub lists results in sorting the entire original list. On a CPU+GPU platform consisting of an Intel i7 980 and an Nvidia GTX 580, our algorithm achieves a 20% gain over the current best known comparison sort result that was published by Davidson et. al. [In Par 2012]. On the above experimental platform, our results are better by 40% on average over a similar GPU-alone algorithm proposed by Leischner et. al. [IPDPS 2010]. Our results also show that our algorithm and its implementation scale with the size of the input. We also show that such performance gains can be obtained on other hybrid CPU+GPU platforms.