Evaluating ISO C++ Parallel Algorithms on Heterogeneous HPC Systems

Abstract

Recent revisions to the ISO C++ standard have added specifications for parallel algorithms. These additions cover common use-cases, including sequence traversal, reduction, and even sorting, many of which are highly applicable in HPC, and thus represent a potential for increased performance and productivity.This study evaluates the state of the art for implementing heterogeneous HPC applications using the latest built-in ISO C++17 parallel algorithms. We implement C++17 ports of representative HPC mini-apps that cover both compute-bound and memory bandwidth-bound applications. We then conduct benchmarks on CPUs and GPUs, comparing our ports to other widely-available parallel programming models, such as OpenMP, CUDA, and SYCL.Finally, we show that C++17 parallel algorithms are able to achieve competitive performance across multiple mini-apps on many platforms, with some notable exceptions. We also discuss several key topics, including portability, and describe workarounds for a number of remaining issues, including index-based traversal and accelerator device/memory management.