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ExHetAI: The Workshop on Extreme Heterogeneity and AI Convergence in HPC

Workshop Overview

The convergence of artificial intelligence (AI) and high-performance computing (HPC), alongside the rapid advancement of heterogeneous computing architectures, is reshaping the landscape of modern supercomputing. Specialized accelerators such as GPUs, TPUs, IPUs, neuromorphic processors, quantum devices, and FPGAs—are driving innovation, but also introducing new challenges in performance portability, system optimization, and software adaptability. In this era of exascale and extreme heterogeneity, fully harnessing diverse hardware platforms demands AI-driven methods, novel programming paradigms, and intelligent workload orchestration. This workshop will bring together researchers and practitioners from academia, industry, and national laboratories to explore cutting-edge developments in AI-HPC integration, heterogeneous system design, energy-efficient computing, and AI-assisted performance tuning. By fostering interdisciplinary dialogue and collaboration, the workshop seeks to drive progress toward scalable, efficient, and sustainable computing. We invite contributions addressing heterogeneous hardware, AI-enabled HPC methodologies, advanced memory architectures, and innovative programming models aiming at shaping the future of AI-driven scientific discovery and high-performance computing.




Workshop Program


ExHetAI 2025 will be held on Sunday, November 16. The schedule is provided below. All times are in CST.

9am - 9:10am CST Opening Remarks
9:10am - 10am CST Invited Talk 1: Memorization vs Reasoning in MoEs and Estimating Memory Consumption in Distributed Training
Rio Yokota
Institute of Science Tokyo
10am - 10:30am CST Morning Break
10:30am - 11:10am CST Invited Talk 2: TBD
Matthew Dearing
Argonne National Laboratory
11:10am - 11:30am CST Enabling Unstructured Sparse Fine-Tuning and Inference for Foundation Models on Wafer-Scale Engine
Haoyu Zheng, Yifan Zeng, Linghao Song, Murali Emani, and Wenqian Dong
Session chair: Seyong Lee
11:30am - 11:50am CST WAGES: Workload-Aware GPU Sharing System for Energy-Efficient Serverless LLM Serving
Tianyu Wang, Gourav Rattihalli, Aditya Dhakal, Xulong Tang, and Dejan Milojicic
Session chair: Seyong Lee
11:50am - 12:10pm CST OmniFed: A Modular Framework for Configurable Federated Learning from Edge to HPC
Sahil Tyagi, Andrei Cozma, Olivera Kotevska, and Feiyi Wang
Session chair: Pedro Valero-Lara
12:10pm - 12:30pm CST Enhancing ChatPORT with CUDA-to-SYCL Kernel Translation Capability
Zheming Jin, Swaroop Pophale, and Keita Teranishi
Session chair: Pedro Valero-Lara
12:30pm CST Closing Remarks

Call for Papers

Topics will include but will not be limited to:

  • AI and HPC Convergence: Application of AI techniques to accelerate scientific computing and enhance HPC workflows; integration of machine learning and data-driven methods into traditional simulation pipelines.;
  • Heterogeneous Architectures for HPC and AI: Design, deployment, and utilization of diverse compute platforms including GPUs, TPUs, FPGAs, neuromorphic processors, quantum devices, and domain-specific accelerators in high-performance environments.;
  • Programming Models and Portability: Frameworks, languages, and tools that enable performance portability and efficient code execution across heterogeneous and evolving architectures.;
  • AI-Assisted System Optimization: Use of AI and machine learning for compiler optimizations, workload scheduling, autotuning, performance modeling, and intelligent resource management in complex systems;
  • Memory and Data Management: Innovations in hierarchical memory systems, data movement optimization, locality-aware computing, and high-performance I/O strategies tailored for heterogeneous platforms;
  • Energy Efficiency and Sustainable HPC: AI-enhanced techniques for reducing energy consumption, managing power-performance trade-offs, and enabling environmentally sustainable supercomputing;
  • Submission

    Authors are invited to submit manuscripts in English structured as technical papers up to 6 pages 2-column pages, min 5 pages (U.S. letter – 8.5″x11″), excluding the bibliography, using the ACM proceedings template that is available at here. The manuscripts are single-blind. Word authors can use the “Interim Layout”. Submissions not conforming to these guidelines may be returned without review.
    All manuscripts will be peer-reviewed and judged on correctness, originality, technical strength, and significance, quality of presentation, and interest and relevance to the workshop attendees. Submitted papers must represent original unpublished research that is not currently under review for any other conference or journal. Papers not following these guidelines will be rejected without review and further action may be taken, including (but not limited to) notifications sent to the heads of the institutions of the authors and sponsors of the conference. Submissions received after the due date, exceeding length limit, or not appropriately structured may also not be considered. At least one author of an accepted paper must register for and attend the workshop. Authors may contact the workshop organizers for more information.
    Papers should be submitted electronically at: https://submissions.supercomputing.org, SC25 Workshop: ExHetAI'25: Workshop on Extreme Heterogeneity and AI Convergence in HPC".
    The final papers will be published in the SC Workshops Proceedings.

    Important Dates

    Submission Deadline

    August 8 (11:59pm, AOE), 2025

    August 15 (11:59pm, AOE), 2025

    Notification of acceptance

    September 5, 2025

    Camera Ready

    September 26, 2025

    Organizers

  • Gokcen Kestor, Barcelona Supercomputing Center
  • Seyong Lee, Oak Ridge National Laboratory, USA
  • Pedro Valero-Lara, Oak Ridge National Laboratory, USA
  • Technical Program Committee

  • Wenqian Dong, Oregon State University
  • Murali Krishna Emani, Argonne National Laboratory
  • Mohamed Ibrahim Ghenai, CERFACS
  • Eduardo Iraola De Acevedo, Barcelona Supercomputing Center
  • Ali Jannesari, Iowa State University
  • Geonhwa Jeong, META
  • Dong Li, UC Merced
  • Guray Ozen, NVIDIA, USA
  • Ivy Peng, KTH Royal Institute of Technology
  • Zhen Peng, Pacific Northwest National Laboratory
  • Jie Ren, William and Marry
  • Catherine Schuman, The University of Tennessee Knoxville