In recent years, a range of novel methods and tools have been developed for the evaluation, design, and modelling of parallel and distributed systems and applications. At the same time, the term ‘performance’ has broadened to include factors like scalability, energy efficiency, reliability, and robustness in addition to the classic resource-oriented notions.

The aim of this topic is to gather researchers working on different aspects of performance modelling, evaluation, and prediction, i.e. systems, tools and applications running on the whole range of parallel and distributed systems (multi-core and heterogeneous architectures, HPC systems, grid and cloud contexts, non-von Neumann architectures, etc.). Authors are invited to submit novel research in all areas of performance modelling, prediction and evaluation, and to help bring together current theory and practice.

Focus

• Design of open and reproducible experiments, metrics, and benchmarks
• Novel techniques and tools for performance measurement, evaluation, and prediction
• Advanced simulation techniques and tools
• Measurements, benchmarking, and tracing for parallel and distributed systems
• Workload and task modelling and traceability
• Performance-driven code optimization
• Verification and validation of performance models
• Performance visualization
• Power consumption modelling and prediction
• Performance modelling, analysis, and prediction for both applications and systems (e.g., grids and cloud computing environments, large-scale HPC platforms)
• Performance modelling and simulation of emerging exascale systems
• Systems software and tools for energy-efficiency and resource management
• Power-efficiency and resource-awareness for petascale and exascale systems
• Performance-oriented and/or energy-aware parallel programming paradigms and models