Heterogeneous Programming for the Homogeneous Majority

Abstract

In order to take advantage of the burgeoning diversity in processors at the frontier of supercomputing, the HPC community is migrating and improving codes to utilise heterogeneous nodes, where accelerators, principally GPUs, are highly prevalent in top-tier supercomputer designs. Programs therefore need to embrace at least some of the complexities of heterogeneous architectures. Parallel programming models have evolved to express heterogeneous paradigms whilst providing mechanisms for writing portable, performant programs. History shows that technologies first introduced at the frontier percolate down to local workhorse systems. However, we expect there will always be a mix of systems, some heterogeneous, but some remaining as homogeneous CPU systems. Thus it is important to ensure codes adapted for heterogeneous systems continue to run efficiently on CPUs. In this study, we explore how well widely used heterogeneous programming models perform on CPU-only platforms, and survey the performance portability they offer on the latest CPU architectures.