Todd Gamblin (LLNL) will be giving the keynote on “Spack and software reproducibility in HPC”.

About REPPAR

The workshop is concerned with experimental practices in parallel computing research. We are interested in research works that address the statistically rigorous analysis of experimental data and visualization techniques of these data. We also encourage researchers to state best practices to conduct experiments and papers that report experiences obtained when trying to reproduce or repeat experiments of others. The workshop also welcomes papers on new tools for experimental computational sciences, e.g., tools to archive large experimental data sets and the source code that generated the (e.g., workflow systems, experimental testbeds).

Scope / Topics of Interest

• Experimental design of parallel computing experiments
• Experiences and best practices for conducting experiments (including papers that address the reproduction of other articles)
• Supporting reproducibility in experimental testbeds for parallel computing
• Tools for reproducible research (e.g., control of experiments, versioning, archiving)
• Analysis of experimental data (e.g., visualization, statistical analysis, provenance)
• Automated uncertainty quantification for experimental workflows (or data-focused workflows)
• Systems to incorporate (potentially very large) data into automated testing frameworks
• Sustainable models for public data sharing
• Ideas on Artifact Evaluation in Distributed Computing and HPC
• Improving the Review process in Parallel Computing
• Open Science and Parallel Computing