一句话：提出基于 HPC 容器的 BeeSwarm，将并行扩展性能测量集成到持续集成环境中。
性能尤其是可扩展性是 HPC 应用的关键指标，但现有 HPC 性能分析工具通常未与 CI 工具集成。本文提出 BeeSwarm，一个基于 HPC 容器的并行扩展性能测量系统，可方便地应用于现有 CI 测试环境，帮助 HPC 应用开发者监测程序在不同计算资源上的扩展表现。作者使用一个多物理场 HPC 应用，在 Travis CI、GitLab CI 和 GitHub Actions 中，并以 ChameleonCloud 与 Google Compute Engine 作为计算后端进行演示。结果表明，BeeSwarm 可用于 HPC 应用的可扩展性与性能测试。
Testing is one of the most important steps in software development–it ensures the quality of software. Continuous Integration (CI) is a widely used testing standard that can report software quality to the developer in a timely manner during development progress. Performance, especially scalability, is another key factor for High Performance Computing (HPC) applications. There are many existing profiling and performance tools for HPC applications, but none of these are integrated into CI tools. In this work, we propose BeeSwarm, an HPC container based parallel scaling performance system that can be easily applied to the current CI test environments. BeeSwarm is mainly designed for HPC application developers who need to monitor how their applications can scale on different compute resources. We demonstrate BeeSwarm using a multi-physics HPC application with Travis CI, GitLab CI and GitHub Actions while using ChameleonCloud and Google Compute Engine as the compute backends. Our results show that BeeSwarm can be used for scalability and performance testing of HPC applications.
DOI 原文 ·
@inproceedings{paperbot6564,
title = {BeeSwarm: Enabling Parallel Scaling Performance Measurement in Continuous Integration for HPC Applications},
author = {Jake Tronge and Jieyang Chen and Patricia Grubel and Tim Randles and Rusty Davis and Quincy Wofford and Steven Anaya and Qiang Guan},
booktitle = {ASE},
year = {2021},
doi = {10.1109/ase51524.2021.9678805}
}