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BeeSwarm: Enabling Parallel Scaling Performance Measurement in Continuous Integration for HPC Applications

Journal Article · · IEEE/ACM International Conference on Automated Software Engineering (Online)
 [1];  [2];  [3];  [3];  [3];  [3];  [3];  [1]
  1. Kent State Univ., Kent, OH (United States)
  2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  3. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
+ Show Author Affiliations

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. Finally, our results show that BeeSwarm can be used for scalability and performance testing of HPC applications.

Research Organization:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)
Grant/Contract Number:
89233218CNA000001
OSTI ID:
1922018
Report Number(s):
LA-UR-22-22138
Journal Information:
IEEE/ACM International Conference on Automated Software Engineering (Online), Journal Name: IEEE/ACM International Conference on Automated Software Engineering (Online) Vol. 2021; ISSN 2643-1572
Publisher:
IEEECopyright Statement
Country of Publication:
United States
Language:
English

References (12)

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Legion: Expressing locality and independence with logical regions
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conference November 2012
The Lightweight Distributed Metric Service: A Scalable Infrastructure for Continuous Monitoring of Large Scale Computing Systems and Applications
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conference November 2014
Including Performance Benchmarks into Continuous Integration to Enable DevOps journal April 2015
Charliecloud: unprivileged containers for user-defined software stacks in HPC conference January 2017
PerfCI conference December 2020

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Related Subjects

97 MATHEMATICS AND COMPUTING
cloud computing
computer science
container
continuous integration
high performance computing
scalability test