high performance computing on graphics processing units: hgpu.org

Although the need for heterogeneous chips in high performance numerical computing was identified by Chillemi and co-authors in 2001 it is only over the past five years that it has emerged as the new frontier for HPC. In this environment one or more accelerators works symbiotically, on each node, with a multi-core CPU. Two such accelerator technologies are FPGA and GPU each of which works with instruction level parallelism. This paper provides a case study on implementing one computational algorithm on each of these heterogeneous environments. The algorithm is the evaluation of two electron integrals using direct numerical quadrature and is drawn from atomic physics. The results of the study show that while each accelerator is viable, there are considerable differences in the implementation strategies that must be followed on each.