The purpose of this workshop is to provide a stable forum for researchers and practitioners dealing with compelling challenges and issues of the software development life cycle on modern parallel platforms and HPC systems. The increased complexity of parallel applications on modern parallel platforms (e.g. multicore/manycore, distributed/hybrid systems) requires more insight into engineering of parallel software for targeting the underlying parallel systems. Rapidly emerging artificial intelligence-related technologies and their application to software engineering and parallel computing systems will be promising approaches to tackle these issues as well as approaches using traditional empirical and experimental methods. The workshop title “AI-Inspired and Empirical Methods for Software Engineering on Parallel Computing Systems” reflects a change from the previous edition with emphasis placed on this trend for rapidly growing research interests on AI-inspired software engineering techniques for performance. We aim to advance the state of the art in all aspects of techniques on software engineering and parallel computing systems such as requirements engineering and software specification; design and implementation; program analysis; performance analysis, profiling and tuning; testing and debugging.
Call for Papers
The goal of the workshop is to present a stimulating environment where ideas, experiences and topics relevant to parallel software engineering and software analytics can be shared/exchanged among researchers and practitioners in the fields of systems, programming, languages and software. The intention of the workshop is to initiate collaborations focused on solving challenges introduced by ongoing research in these topics. Through Q&A sessions, presenters have the opportunity to receive feedback and opinions of other domain experts as well as to discuss obstacles and promising approaches in current research. Both authors and attendees can discover new ideas and new directions for parallel programming research.
Specific topics of interest include, but are not limited to: • AI and machine learning for parallel programming and high-performance computing • Software analytics for parallel programs • Tools and environments for all aspects of engineering parallel software and their enhancement through AI-related technologies • High performance deep learning • Design of parallel programs and parallel design patterns • Software development process and requirement engineering of parallel software • Parallel software architectures • Performance modeling techniques on parallel systems • Profiling and event trace analysis • Refactoring and reengineering • Performance tuning and auto-tuning • Energy-efficient parallel computing • Testing and debugging of parallel applications • Case studies and experience reports
The format of the workshop would be a full-day mini-conference. We welcome original, unpublished regular papers (10 pages) and short papers (4 pages) on current research, and position papers (max. 2 pages) including industrial and practical experiences, tool presentations/demonstration, early results & novel ideas without a comprehensive/extensive evaluation, preliminary and exploratory work with unconventional approaches or wild and crazy ideas. We intend to publish accepted papers as proceedings in the ACM Digital Library.