Closing a Source Complexity Gap between Chapel and HPX

Abstract

A previous case study measured performance vs source-code complexity across multiple languages. The case study identified Chapel and HPX provide similar performance and code complexity. This paper is the result of initial steps toward closing the source-code complexity gap between Chapel and HPX by using a source-to-source compiler. The investigation assesses the single-machine performance of both Chapel and Chplx applications across Arm and x86.

References in corpus (3)

• Improving the scalability of parallel N-body applications with an event driven constraint based execution model
• Benchmarking the Parallel 1D Heat Equation Solver in Chapel, Charm++, C++, HPX, Go, Julia, Python, Rust, Swift, and Java
• Evaluating HPX and Kokkos on RISC-V using an Astrophysics Application Octo-Tiger

Cited by in corpus (1)

• A New Execution Model and Executor for Adaptively Optimizing the Performance of Parallel Algorithms Using HPX Runtime System