[hpc-announce] CFP: The 2nd International Workshop on Foundational large Language Models Advances for HPC (LLM4HPC), co-located with ISC-HPC'26, Hamburg, Germany

[Valero Lara, Pedro]

LLM4HPC 2026
The 2nd International Workshop on Foundational large Language Models Advances for HPC
https://urldefense.us/v3/__https://ornl.github.io/events/llm4hpc2026/__;!!G_uCfscf7eWS!f_w5DZZGnmNbxFI-8pjuHTWYnA48WOjgkV5man5HBNpMFhwcst1HgsztzAoYhyjvwibLYczxHUj9hvllV7_ABfxrHdVNqg$ 

to be held in conjunction with
ISC-HPC 2026

26 June, 2026
Hamburg, Germany

—Introduction

Since their development and release, modern Large Language Models (LLMs), such as the Generative Pre-trained Transformer (GPT) model and the Large Language Model Meta AI (LLaMA), have come to signify a revolution in human-computer interaction spurred on by their high-quality results. LLMs have repaved this landscape thanks to unprecedented investments and enormous training models (hundreds of billions of parameters). The availability of LLMs has led to increasing interest in how they could be applied to a large variety of applications. The HPC community made recent research efforts to evaluate current LLM capabilities for some HPC tasks, including code generation, auto parallelization, performance portability, correctness, among others. All these studies concluded that state-of-the-art LLM capabilities have proven so far insufficient for these targets. Hence, it is necessary to explore novel techniques to further empower LLMs to enrich the HPC mission and its impact.

—Call For Papers

—Objectives, scope and topics of the workshop

This workshop objectives are focused on LLMs advances for any HPC major priority and challenge with the aims to define and discuss the fundamentals of LLMs for HPC-specific tasks, including but not limited to hardware design, compilation, parallel programming models and runtimes, application development, enabling LLM technologies to have more autonomous decision-making about the efficient use of HPC. This workshop aims to provide a forum to discuss new and emerging solutions to address these important challenges towards an AI-assisted HPC era. Papers are being sought on many aspects of LLM for HPC targets including (but not limited to):


  *
LLMs for Programming Environments and Runtime Systems
  *
LLMs for HPC and Scientific Applications
  *
LLMs for Hardware design (including non-von Neumann Architectures)
  *
Reliability/Benchmarking/Measurements for LLMs

—Program (TBD)

—Important Dates

  *
Paper submission deadline : March 6, 2026
  *
Notification of acceptance : March 23, 2026
  *
Camera-ready papers due : May 15, 2026
  *
Workshop day: June 26, 2026

—Steering Committee
Jeffrey S. Vetter, Oak Ridge National Laboratory, USA
Franz Franchetti, Carnegie Mellon University, USA
Abhinav Bhatele, University of Maryland, USA

—Organizers (Contact us)
Pedro Valero-Lara (chair)
Oak Ridge National Laboratory, USA
valerolarap at ornl.gov

Simon Garcia de Gonzalo (co-chair)
Sandia National Laboratory, USA
simgarc at sandia.gov

Ignacio Laguna (co-chair)
Lawrence Livermore National Laboratory, USA
lagunaperalt1 at llnl.gov

Upasana Sridhar (co-chair)
Carnegie Mellon University, USA
upasanas at andrew.cmu.edu

—Programme Committee
Bogdan Nicolae, Argonne National Laboratory, USA
Aaron Young, Oak Ridge National Laboratory, USA
Elias Werner, Technische Universitat Dresden, Germany
Upasana Sridhar, Carnegie Mellon University, USA
Hiroyuki Takizawa, Tohoku University, Japan
Olivier Aumage, INRIA, France
Monil Mohammad Alaul Haque, Oak Ridge National Laboratory, USA
Patrick Diehl, Los Alamos National Laboratory, USA
Xingfu Wu, Argonne National Laboratory, USA
Eduardo Iraola, Barcelona Supercomputing Center, Spain
Zhiling Lan, University of Illinois Chicago, USA
Noujoud Nader, Louisiana State University, USA
Daichi Mukunoki, Nagoya University, Japan
Keita Teranishi, Oak Ridge National Laboratory, USA
Tuning Xia, Rice University, USA
Charlie Catlett, Argonne National Laboratory, USA
Swaroop Pophale, Oak Ridge National Laboratory, USA
Chris Siefert, Sandia National Laboratory, USA
Takahiro Katagiri, Nagoya University, Japan
Het Mankad, Oak Ridge National Laboratory, USA
William Godoy, Oak Ridge National Laboratory, USA

—Manuscript submission

We invite submissions of original, unpublished research and experiential papers. Papers should be between 6 to 12 pages in length (including a bibliography and appendices, with two possible extra pages after the review to address the reviewer’s comments), formatted according to Springer’s Lecture Notes in Computer Science (LNCS). All paper submissions will be managed electronically via ISC-HPC Linklings.

—Proceedings
All accepted papers will be published in the ISC-HPC Workshops 2025 proceedings by SpringerLink.

—Best Paper Award

The Best Paper Award will be selected on the basis of explicit recommendations of the reviewers and their scoring towards the paper’s originality and quality.

—Keynote Speaker (Daichi Mukunoki, Nagoya University):
Exploring Multi-Agent Systems for HPC Code Development
Recent advances in code generation AI have demonstrated remarkable potential to transform software development. However, applying these technologies to the high-performance computing (HPC) domain remains challenging. HPC code requires not only functional correctness but also a range of additional considerations, such as architecture-specific performance optimization, support for GPUs and Fortran, appropriate algorithm selection tailored to the target environment, and careful control of numerical accuracy. At the Information Technology Center of Nagoya University, we are advancing HPC-GENIE, a research and development project focused on applying generative AI to HPC code development. Rather than developing new models, we concentrate on designing AI agents built on existing models. In particular, we explore the potential of multi-agent systems in which multiple specialized agents collaborate to address complex HPC development tasks. We are also developing lightweight systems that operate entirely in local environments without relying on commercial services. In this talk, we discuss the current challenges and future prospects of AI-driven agents for HPC code development.

Daichi Mukunoki is an Assistant Professor at the Information Technology Center, Nagoya University. He held research positions at the RIKEN Center for Computational Science from 2014 to 2023, serving as a Postdoctoral Researcher and later as a Research Scientist. He was also a Postdoctoral Research Fellow at Tokyo Woman’s Christian University and a JSPS Research Fellow at the University of Tsukuba, where he received his Ph.D. in Engineering in 2013. His research interests include GPU computing, numerical computing, mixed-precision algorithms, computer arithmetic, and code-generative AI.

—Registration

Information about registration at ISC-HPC 2025 website.


Get Outlook for Mac <https://urldefense.us/v3/__https://aka.ms/GetOutlookForMac__;!!G_uCfscf7eWS!f_w5DZZGnmNbxFI-8pjuHTWYnA48WOjgkV5man5HBNpMFhwcst1HgsztzAoYhyjvwibLYczxHUj9hvllV7_ABfz4tHyMnQ$ >