In recent years, the convergence of high-performance computing and eScience has opened new scientific discovery and innovation avenues. Researchers across various domains leverage advanced computational techniques to analyze vast data, simulate complex systems, and accelerate scientific workflows.
The 3rd Workshop on High-Performance eScience (HiPES) aims to bring together experts from academia, industry, and government organizations to discuss the latest developments in this rapidly evolving field and explore emerging trends, challenges, and opportunities within the framework of tools and applications.
The workshop focuses on managing distributed workflows in eScience, encompassing a broad spectrum of topics essential for interoperability and efficiency. This includes exploring design patterns, languages, and orchestration tools tailored to the specific needs of eScience high-performance applications. Additionally, researchers delve into scheduling algorithms, fault tolerance mechanisms, performance monitoring, and benchmarking procedures to ensure the smooth functioning of distributed workflows across diverse scientific domains.
Emphasizing the concept of FAIRness (Findable, Accessible, Interoperable, and Reusable), the workshop encourages contributors to explore this crucial aspect of eScience. Methodologies and tools are discussed to ensure data and computational resources are discoverable, accessible, and usable across various platforms and research communities. Privacy and security considerations, particularly concerning sensitive scientific data, are integral components open for discussion during the workshop.
The workshop will feature invited talks, contributed presentations, and panel discussions.
+We invite submissions of original research contributions, case studies, and innovative applications in the following areas (but not limited to):
• High-performance computing (HPC) techniques and architectures for eScience
• Languages, paradigms, and tools for scientific workflows
• Scalable and efficient scientific workflows orchestration for eScience
• Optimization techniques for parallel and distributed computing
• Integration of machine learning and AI with eScience applications
• Big data analytics and visualization in scientific domains
• Cloud computing and edge computing for eScience
• Reproducibility and sustainability in computational research
• Performance evaluation and benchmarking of eScience tools and platforms
• Paradigms and techniques for FAIRness in eScience
• Ad-hoc file systems for I/O intensive eScience applications
• Prospective and retrospective provenance models for large-scale applications
• Security, privacy, and trust models and tools for eScience platforms
• Case studies and success stories of real-world eScience applications
We encourage submissions of full papers describing original research, work-in-progress, or experience reports related to the workshop topics.
+Important dates:
+Paper submission: May 10
Notification of acceptance: June 22
Camera-ready: July 3