high performance computing on graphics processing units: hgpu.org

The proliferation of heterogeneous computing systems presents the parallel computing community with the challenge of porting legacy and emerging applications to multiple processors with diverse programming abstractions. OpenCL is a vendor-agnostic and industry-supported programming model that offers code portability on heterogeneous platforms, allowing applications to be developed once and deployed "anywhere". In this paper, we use the OpenCL implementation of the Open-Dwarfs, a benchmark suite that captures patterns of computation and communication common to classes of important applications, as delineated by Berkeley’s Dwarfs. We evaluate portability across multicore CPU, GPU, APU (CPUs+GPUs on a die), the Intel Xeon Phi co-processor, and the FPGA. To realize FPGA portability, we exploit SOpenCL (Silicon OpenCL), a CAD tool that automatically converts OpenCL kernels to customizable hardware accelerators. We show that a single, unmodified OpenCL code base, i.e., OpenDwarfs, can be effectively used to target multiple, architecturally diverse platforms.