Spinner: Enhancing HPC Experimentation with a Streamlined Parameter Sweep Tool

Author(s)

Ceccato, Rodrigo ; Cleto, Jhonatan ; Leite, Gustavo ; Rigo, Sandro ; Monsalve Diaz, Jose M. ; Yviquel, Herve

• Document type: Journal article
• Source: 2024 INTERNATIONAL SYMPOSIUM ON COMPUTER ARCHITECTURE AND HIGH PERFORMANCE COMPUTING WORKSHOPS, SBAC-PADW; v. N/A, p. 11-pg., 2024-01-01.

Abstract

We introduce Spinner, an open-source, parameterized sweep benchmark tool for high-performance computing (HPC). Spinner employs a YAML file format to facilitate the execution of applications, data collection, and metadata versioning and sharing. This setup simplifies version control and sharing of experimental configurations. By including dataframes that describe experiments and raw data, it allows readers and reviewers to gain a clearer understanding than summary statistics alone. Spinner's design is non-intrusive and efficient, executing user-supplied commands and dynamically replacing parameters in the command template. It also features the capability to rerun failed experiments, which is particularly useful for testing unstable applications or identifying unstable parameter combinations. We have demonstrated Spinner's functionality with minimal configuration by using it in tests with LAMMPS, GROMACS, Task Bench, XSBench, and RSBench on two different clusters. These tests measured wall time and captured application outputs, underscoring Spinner's practicality and adaptability. (AU)

• FAPESP's process: 24/04232-8 - Implementation and Optimization of Task Offloading in Heterogeneous Clusters using OpenMP Cluster
• Grantee: Jhonatan Cléto
• Support Opportunities: Scholarships in Brazil - Master
• FAPESP's process: 19/17874-0 - Multi-user Equipmente approved in grant 2013/08293-7, KAHUNA upgrade - HPE Apollo Gen10 supercomputer
• Grantee: Munir Salomao Skaf
• Support Opportunities: Multi-user Equipment Program
• FAPESP's process: 13/08293-7 - CCES - Center for Computational Engineering and Sciences
• Grantee: Munir Salomao Skaf
• Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC
• FAPESP's process: 20/08475-1 - Increasing efficiency of task parallelism in GPU clusters for scientific workloads
• Grantee: Gustavo Leite
• Support Opportunities: Scholarships in Brazil - Doctorate