Held in conjunction with SC24: The
International Conference for High
Performance Computing, Networking, Storage, and
Analysis, and in
cooperation with the IEEE Computer Society (IEEE CS)
and the Association for Computing Machinery (ACM).
Agenda
Will be posted after final papers have been accepted.
Overview
LLVM has become an integral part of the software-development ecosystem for optimizing compilers, dynamic-language execution engines, source-code analysis and transformation tools, debuggers and linkers, and a whole host of programming-language and toolchain-related components. The recent surge in AI development has further proven the efficacy of the LLVM infrastructure as many predominant AI/ML compilation systems deployed in practice leverage the MLIR framework to exploit high level semantics provided by their frontends, while maintaining a production grade and high performance software stack. Research in, and implementation of, program analysis, compilation, execution, and profiling has clearly benefited from the availability of a high-quality, freely-available infrastructure on which to build. This workshop will focus on recent developments, from both academia and industry, that build on LLVM to advance the state of the art in high-performance computing.
Format
This workshop will feature contributed papers and an invited talk focusing on recent developments that build on LLVM to advance the state of the art in high-performance computing.
Topics of interest include, but are not limited to:
- Compiler design for highly-concurrent/parallel environments
- Compilation techniques targeted at high-performance computing codes
- Programming-language implementation techniques enabling high performance and high productivity
- Embedding compilation and dynamic execution at scale
- Tools for optimization, profiling, and feedback
- Source code transformation and analysis
- Gap analyses of open-source LLVM-based tools
- Domain-specific compilation and optimization
Please note: All particpants (authors, presenters, committee members, and attendees alike) are expected to follow both the LLVM Code of Conduct as well as the relevant SC24 conduct policies.
Deadlines
- Paper submissions due: August 16, 2024 (AoE)
- Notification to authors of acceptance: September 6, 2024
- Camera-ready papers due: September 27, 2024
- Workshop takes place: November 18, 2024
Please see the SC24 home page for registration deadlines and other information associated with the parent event. Pending the acceptance of the final workshop proceedings, the selected papers will be published by IEEE Xplore.
Submissions
Please submit papers using the SC24 Submissions system by selecting the "Workshops: LLVM-HPC Full Papers" form. Submissions are limited to minimum 6, maximum 10 two-column pages, excluding the bibliography, using the IEEE proceedings template. Please prepare your submissions for single blind review.
Organizers
- James Brodman, Intel
- Johannes de Fine Licht, NextSilicon
- Ryan Kabrick, Tactical Computing Laboratories
- Alexis Perry-Holby, Los Alamos National Laboratory
Program Committee
- Madhur Amilkanthwar, NVIDIA
- James Brodman, Intel Corporation
- Sunita Chandrasekaran, University of Delaware
- Johannes de Fine Licht, NextSilicon
- Christian DeLozier, US Naval Academy
- Tobias Grosser, University of Edinburgh
- Mary Hall, University of Utah
- Ryan Kabrick, Tactical Computing Labs, LLC
- Alice Koniges, University of Hawaii, Maui HPC Center
- John Leidel, Tactical Computing Labs, LLC
- Patrick McCormick, Los Alamos National Laboratory
- Cameron McInally, NVIDIA
- Alexis Perry-Holby, Los Alamos National Laboratory
- Tarun Prabhu, Los Alamos National Laboratory
- Nirmal Prajapati, Los Alamos National Laboratory
- Nadav Rotem, Facebook
- Amalee Wilson, Stanford Univeristy
- Frank Winter, Thomas Jefferson National Accelerator Facility
- Michael Wong, Codeplay Software Ltd., Khronos Group Inc.
- Alex Zinenko, Google
Contact Information
Alexis Perry-Holby (aperry@lanl.gov)
James Brodman (james.brodman@intel.com)
Ryan Kabrick (rkabrick@tactcomplabs.com)
Johannes de Fine Licht (definelicht@inf.ethz.ch)