Held in conjunction with SC22: 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
| Time (CST) | Speaker | Title |
|---|---|---|
| 8:30 | John Leidel | Welcome |
| 8:31 | William Moses | Invited Talk: Polygeist MLIR Frontend for C or C++ |
| 9:00 | Martin Herbordt | Reinforcement Learning Strategies for Compiler Optimization in High Level Synthesis |
| 9:30 | Shalini Jain | Reinforcement Learning assisted Loop Distribution for Locality and Vectorization |
| 10:00 | Coffee | Break |
| 10:30 | Rafael A. Herrera Guaitero | Automatic Asynchronous Execution of Synchronously Offloaded OpenMP Target Regions |
| 11:00 | Damian Rouson | Caffeine: CoArray Fortran Framework of Efficient Interfaces to Network Environments |
| 11:30 | Shilei Tian | Direct GPU Compilation and Execution for Host Applications with OpenMP Parallelism |
| 12:00 | The | End |
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. Now heavily used in both academia and industry, where it allows for rapid development of production-quality tools, LLVM is increasingly used in work targeted at high-performance computing. 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
Deadlines
- Paper submissions due: August 22, 2022 (AoE)
- Notification to authors of acceptance: September 9, 2022
- Camera-ready papers due: October 14, 2022
- Workshop takes place: November 13, 2022
Please see the SC22 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 SC22 Submissions system by selecting the "SC22 Workshop: LLVM-HPC2022 Full Papers" form. Papers must be in IEEE conference format (templates are available). Papers should be no more than 12 pages (including references and figures) and must be at least 8 pages long. Please also note IEEE's Article-Posting Policy.
Organizers
- James Brodman, Intel
- John D. Leidel, Tactical Computing Laboratories
- Patrick McCormick, Los Alamos National Laboratory
- Alexis Perry-Holby, Los Alamos National Laboratory
Program Committee
- Madhur Amilkanthwar, NVIDIA
- James Brodman, Intel Corporation
- Sunita Chandrasekaran, University of Delaware
- Albert Cohen, Google
- Christian DeLozier, US Naval Academy
- Tobias Grosser, University of Edinburgh
- Mary Hall, University of Utah
- Alice Koniges, University of Hawaii, Maui HPC Center
- John Leidel, Tactical Computing Labs, LLC
- Patrick McCormick, Los Alamos National Laboratory
- Cameron McInally, NVIDIA
- EunJung Park, Qualcomm Inc.
- Alexis Perry-Holby, Los Alamos National Laboratory
- Nirmal Prajapati, Los Alamos National Laboratory
- Nadav Rotem, Facebook
- Amalee Wilson, Stanford University
- Frank Winter, Thomas Jefferson National Accelerator Facility
- Michael Wong, Codeplay Software Ltd., Khronos Group Inc.
Contact Information
Alexis Perry-Holby (aperry@lanl.gov)