Abstraction of Programming Models Across Multi-Core and GPGPU Architectures

Work in the field of application acceleration devices is showing great promise, but still remains a tool largely for computer scientists with domain knowledge, given the complexity of porting existing algorithms to new architectures or environments. Such porting is hindered by the lack of abstraction available. We present our latest work in the development of a novel solution to this abstraction problem; an intelligent semi-automatic porting system. This allows a higher level of abstraction where the user does not have to intervene or annotate their source code, while maintaining reasonable levels of performance. We present comparisons between manual and automatic code ports on two different platforms (NVIDIA CUDA and ClearSpeed C-n), showing the versatility of this approach.