A Case Study for Performance Portability Using OpenMP 4.5

Abstract

In recent years, the HPC landscape has shifted away from traditional multi-core CPU systems to energy-efficient architectures, such as many-core CPUs and accelerators like GPUs, to achieve high performance. The goal of performance portability is to enable developers to rapidly produce applications which can run efficiently on a variety of these architectures, with little to no architecture specific code adoptions required. We implement a key kernel from a material science application using OpenMP 3.0, OpenMP 4.5, OpenACC, and CUDA on Intel architectures, Xeon and Xeon Phi, and NVIDIA GPUs, P100 and V100. We will compare the performance of the OpenMP 4.5 implementation with that of the more architecture-specific implementations, examine the performance of the OpenMP 4.5 implementation on CPUs after back-porting, and share our experience optimizing large reduction loops, as well as discuss the latest compiler status for OpenMP 4.5 and OpenACC.