1 INTRODUCTION
2 DEFINITIONS OF REPRODUCIBLE RESEARCH
2.1 Evolution in terminologies
2.2 Importance of reproducible research
3 REPRODUCIBILITY CRISIS: EXAMPLES FROM DIFFERENT DOMAINS
4 OPPOSITION TO THE REPRODUCIBLE RESEARCH MOVEMENT
5 WHY DO WE LOSE REPRODUCIBILITY?
5.1 Open Science
5.2 Documentation
5.3 Statistics
5.4 Scientific culture
5.5 Software environment
5.6 Workflow
5.7 Software engineering
6 REPRODUCIBILITY PROBLEMS SPECIFIC TO HPC
6.1 Parallel computing
6.2 PRNGs and Monte Carlo simulations
6.3 Optimization
6.4 Hardware heterogeneity
6.5 Quantum computing
6.6 Machine learning
6.7 Silent errors and other soft errors
7 WHAT ARE THE SOLUTIONS PROPOSED TO ENHANCE REPRODUCIBILITY?
7.1 Versioning and archiving
7.2 Literate programming and documentation
7.3 Workflow
7.4 Software environment
7.5 Parallel computing
7.6 How do we deal with silent or 'soft errors'
8 UNRESOLVED PROBLEMS IN REPRODUCIBLE RESEARCH FOR HPC
8.1 Portability of algorithms and particularly PRNGs
8.2 Data Reproducibility in Big Data Infrastructures
8.3 Performance Reproducibility and Optimization
8.4 Education, Community Collaboration, and Workflow Integration
8.5 Addressing Reproducibility in Emerging Computational Models
CONCLUSION