Held in conjunction with SC23: 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 (MST) | Speaker | Title |
|---|---|---|
| 9:00 | James Brodman and Ryan Kabrick | Welcome |
| 9:01 | Shilei Tian | OpenMP Kernel Language Extensions for Performance Portable GPU Codes |
| 9:31 | Sergio Iserte | DPU Offloading Programming with the OpenMP API |
| 10:00 | Coffee | Break |
| 10:30 | Nick Brown | Fortran performance optimisation and auto-parallelisation by leveraging MLIR-based domain specific abstractions in Flang |
| 11:00 | Anton Rydahl | Precision and Performance Analysis of C Standard Math Library Functions on GPUs |
| 11:30 | Marcin Copik | Lightning Talk - Cppless: Productive and Performant Serverless Programming in C++ |
| 11:37 | Alister Johnson | Lightning Talk - Automating Loop Optimization with Code Samples and AST Matching |
| 11:44 | Camille Coti | Lightning Talk - Just-in-Time Autotuning |
| 11:51 | Christopher Taylor | Lightning Talk - META: A Toolkit for Template Metaprogramming Performance Analysis |
| 11:58 | James Brodman, Sergio Iserte, Nick Brown, Anton Rydahl | Panel Discussion | 12:28 | James Brodman and Ryan Kabrick | Closing Remarks |
| 12:30 | 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
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 SC23 conduct policies.
Deadlines
- Paper submissions due: August 16, 2023 (AoE)
- Notification to authors of acceptance: September 8, 2023
- Camera-ready papers due: September 29, 2023
- Workshop takes place: November 12, 2023
Please see the SC23 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 SC23 Submissions system by selecting the "SC23 Workshop: LLVM-HPC2023 Full Papers" form. Papers must use the new proceedings templates and the CCS2012 guide (available here), should be no more than 12 pages (including references and figures), and must be at least 6 pages long.
Organizers
- James Brodman, Intel
- Ryan Kabrick, 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
- Christian DeLozier, US Naval Academy
- Tobias Grosser, University of Edinburgh
- Mary Hall, Univeristy 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)
Ryan Kabrick (rkabrick@tactcomplabs.com)
James Brodman (james.brodman@intel.com)
Pat McCormick (pat@lanl.gov)