Join leading researchers, practitioners, and innovators in exploring the convergence of Artificial Intelligence and High Performance Computing. Submit your original research and be part of shaping the future of technology.
Original contributions are sought in topics under the theme: AI, HPC, and Resilient Systems
Manuscripts should be submitted as a single PDF (Full papers: 12–15+ Pages), following LNCS format through EDAS at https://edas.info/N33622
Submit via EDASFinal deadline for submitting full papers through EDAS system. No extensions will be granted.
Authors will be notified about acceptance status and reviewer feedback via email.
Submit final camera-ready version incorporating all reviewer comments and suggestions.
Early bird registration closes. At least one author must register for paper to be published.
Three days of inspiring talks, workshops, and networking opportunities
Follow these guidelines to ensure your submission meets all requirements
All accepted and presented papers will be submitted for inclusion into IEEE Xplore subject to IEEE Xplore’s scope and quality requirements. All papers must be written in English.
Prior to double-blind review, scope and formatting will be checked. Non-compliant papers will be rejected, including:
Authors must not include names, affiliations, emails, acknowledgements, or grant information. Previous works should be referred to in third-person.
AI tools may be used responsibly to enhance research and writing quality, especially for non-native English speakers. Authors must follow IEEE guidelines on AI-generated content disclosure.
Conference encourages full papers only. Maximum length is six (06) A4 pages using the IEEE Template format.
Meet the distinguished academics and industry leaders organizing this conference
General Chair
Carnegie Mellon University
Leading expert in distributed systems and cloud computing with over 25 years of research experience. Former director of NSF Computer Systems Research.
General Co-Chair
UC Berkeley
Pioneer in neural network architectures and deep learning optimization. Recipient of the ACM Grace Murray Hopper Award for contributions to AI.
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