Welcome to the PAW-ATM Workshop.
- Program
- Important dates
- Summary
- Scope and Aims
- Topics
- Submissions
- Organization
- Previous Instances of PAW-ATM
- 9:00 - 9:02 Karla V. Morris Wright, Elliott Slaughter,
Engin Kayraklioglu, Irene Moulitsas, Bill Long, Daniele Lezzi and Kenjiro Taura
PAW-ATM2024 Introduction
(Presentation)
- 9:02 - 10:00 Session 1 Session Chair: Brad Richardson – Lawrence Berkeley National Laboratory
- 9:02 - 9:45 Survey of Technologies for Developers of Parallel Applications
Wonchan Lee – NVIDIA (Presentation)
Damian Rouson – Lawrence Berkeley National Laboratory (Presentation)
- 9:45 - 10:00 Jonas Posner
User Experience: “Resource Adaptivity at Task-Level” Jonas Posner
(Presentation,
Abstract)
- 10:00 - 10:30 Morning Break (30 min)
- 10:30 - 12:30 Session 2 Session Chair: Quincey Koziol – NVIDIA
- 10:30 - 10:50 Torben Kalkhof, and Andreas Koch
Speeding-Up LULESH on HPX: Useful Tricks and Lessons Learned using a Many-Task-Based Approach
(Presentation)
- 10:50 - 11:10 Ryan D. Friese, Roberto Gioiosa, Joseph Cottam, Erdal Mutlu, Gregory Henselman-Petrusek, Polykarpos Thomadakis, and Mark Raugas
Lamellar: A Rust-based Asynchronous Tasking and PGAS Runtime for High Performance Computing
(Presentation)
- 11:10 - 11:30 Fernando Vazquez-Novoa, Daniele Lezzi, Francesc Lordan, Fatemeh Baghdadi, and Davide Cirillo
Applying a Task-Based Approach to Distributed Machine Learning Workflows
(Presentation)
- 11:30 - 11:50 Yuxin Chen, Aydin Buluc, Katherine Yelick, and John Owens
Accelerating Multi-GPU Embedding Retrieval with PGAS style Communication for Deep Learning Recommendation Systems
(Presentation)
- 11:50 - 12:10 Kyle Klenk, Mohammad Mahdi Moayeri, Junwei Guo, Martyn P. Clark, and Raymond J. Spiteri
Mitigating synchronization bottlenecks in high-performance actor-model-based software
(Presentation)
- 12:10 - 12:30 Alex Brooks, Philip Marshall, David Ozog, Md. Wasi-ur- Rahman, Lawrence Stewart, and Rithwik Tom
Intel SHMEM: GPU-initiated OpenSHMEM using SYCL
(Presentation)
- 12:30 - 2:00 Lunch Break (90 min)
- 2:00 - 3:00 Session 3 Session Chair: Kate Rasmuseen - Lawrence Berkeley National Laboratory
- 2:00 - 2:45 Distinguished Speaker: Eric Laurendeau – Polytechnique Montreal A case study for using Chapel within the global aerospace industry
- 2:45 - 3:00 Michael P. Ferguson, Bonnie Hurwitz, and Shreyas Khandekar User Experience: “Exploring Suffix Array Algorithms in Chapel”
- 3:00 - 3:30 Afternoon Break (30 min)
- 3:30 - 3:45 Session 4 Session Chair: Laxmikant Kale - University of Illinois
- 3:45 - 5:30 Panel Discussion: Alternative programming models for applications at scale Panel Chair: Christine Sweeney – Los Alamos National Laboratory
- Jan Ciesko – Sandia National Laboratories
- Nils Deppe – Cornell University
- Jason DeVinney – Center for Computing Sciences
- Eric Laurendeau – Polytechnique Montreal
- Julian Samaroo – Massachusetts Institute of Technology
- Manuscript Submissions deadline:
July 24, 2024July 31, 2024 - Artifact Description (AD) Stage 1 (mandatory) Submissions deadline:
July 24, 2024July 31, 2024 - Notification to authors: August 30, 2024
- Artifact Evaluation (AE) Stage 2 (optional) Submissions deadline: September 4, 2024
- AE and Reproducibility Badges review period: September 5–25, 2024
- Presenters Video Consent Forms: September 20, 2024
- Camera-ready papers with AD/AE appendix due from authors: September 26, 2024
- Final program: September 27, 2024
- Final AD/AE/Badges decisions and notification to authors: September 26, 2024
- PAW-ATM workshop date: November 17, 2024
- Novel application development using high-level parallel programming languages and frameworks
- Examples that demonstrate performance, compiler optimization, error checking, and reduced software complexity
- Applications from artificial intelligence, data analytics, bioinformatics, and other novel areas
- Performance evaluation of applications developed using alternatives to MPI+X and comparisons to standard programming models
- Novel algorithms enabled by high-level parallel abstractions
- Experience with the use of new compilers and runtime environments
- Libraries using or supporting alternatives to MPI+X
- Benefits of hardware abstraction and data locality on algorithm implementation
- Full-length papers presenting novel research results:
- User experience abstracts:
- Karla Vanessa Morris Wright - Sandia National Laboratories
- Engin Kayraklioglu - Hewlett Packard Enterprise
- Kenjiro Taura - University of Tokyo
- Bill Long - Hewlett Packard Enterprise
- Daniele Lezzi - Barcelona Supercomputing Center
- Marjan Asgari - National Resources Canada
- Scott Baden - University of California, San Diego
- Dan Bonachea - Lawrence Berkeley National Laboratory
- Jan Ciesko - Sandia National Laboratory
- Nelson Dias - Federal University of Paraná
- Mario Di Renzo - University of Salento
- David Eberius - Intel
- Engin Kayraklioglu - Hewlett Packard Enterprise
- Daniele Lezzi - Barcelona Supercomputing Center
- Bill Long - Hewlett Packard Enterprise
- Francesc Lordan - Barcelona Supercomputing Center
- Henry Monge Camacho - Oak Ridge National Laboratory
- Karla V. Morris Wright - Sandia National Laboratories
- Irene Moulitsas - Cranfield University
- Catherine Olschanowsky - Advanced Micro Devices, Inc
- Tom Quinn - University of Washington
- Michel Schanen - Argonne National Laboratory
- Michael Schlottke-Lakemper - University of Augsburg
- Elliott Slaughter - SLAC National Accelerator Laboratory
- Kenjiro Taura - University of Tokyo
- Thiago Teixeira - Intel
- Jana Thayer - SLAC National Accelerator Laboratory
- Miwako Tsuji - Riken Advanced Institute for Computational Science
- Irene Moulitsas - Cranfield University
- Elliott Slaughter - SLAC National Accelerator Laboratory
- Oliver Alvarado Rodriguez - New Jersey Institute of Technology
- Desmond Bisandu - Cranfield University
- Yakup Budanaz - ETH Zurich
- Fabio Durastante - University of Pisa
- Guillaume Helbecque - University of Lille
- Mert Hidayetoglu - Stanford University
- Boyu Neil Kuang - Cranfield University
- Seema Mirchandaney - Stanford University
- Soren Rasmussen - National Center for Atmospheric Research
- Kate Rasmuseen - Lawrence Berkeley National Laboratory
- Anjiang Wei - Stanford University
- Bradford L. Chamberlain - Hewlett Packard Enterprise
- Damian W. I. Rouson - Lawrence Berkeley National Laboratory
- PAW-ATM2024: Parallel Applications Workshop, Alternatives To MPI+X
- PAW-ATM2023: Parallel Applications Workshop, Alternatives To MPI+X
- PAW-ATM2022: Parallel Applications Workshop, Alternatives To MPI+X
- PAW-ATM2021: Parallel Applications Workshop, Alternatives To MPI+X
- PAW-ATM2020: Parallel Applications Workshop, Alternatives To MPI+X
- PAW-ATM2019: Parallel Applications Workshop, Alternatives To MPI+X
- PAW-ATM2018: Parallel Applications Workshop, Alternatives To MPI
- PAW2017: PGAS Applications Workshop
- PAW2016: PGAS Applications Workshop
(Presentation, Abstract)
(Presentation, Abstract)
- 3:30 - 3:45 Baboucarr Dibba, Katherine Rasmussen, Brad Richardson, Damian Rouson, David Torres, Yunhao Zhang, Ethan Gutmann, Kareem Ergawy and Michael Klemm
User Experience: “Just Write Fortran: Experiences with a Language-Based Alternative to MPI+X”
(Presentation, Abstract)
(Panel Slides)
Panelists:
Important dates
Summary
As supercomputers become more and more powerful, the number and diversity of applications that can be tackled with these machines grows. Unfortunately, the architectural complexity of these supercomputers grows as well, with heterogeneous processors, multiple levels of memory hierarchy, and many ways to move data and synchronize between processors. The MPI+X programming model, use of which is considered by many to be standard practice, demands that a programmer be expert in both the application domain and the low-level details of the architecture(s) on which that application will be deployed, and the availability of such superhuman programmers is a critical bottleneck. Things become more complicated when evolution and change in the underlying architecture translates into significant re-engineering of the MPI+X code to maintain performance.
Numerous alternatives to the MPI+X model exist, and by raising the level of abstraction on the application domain and/or the target architecture, they offer the ability for “mere mortal” programmers to take advantage of the supercomputing resources that are available to advance science and tackle urgent real-world problems. However, compared to the MPI+X approach, these alternatives generally lack two things. First, they aren’t as well known as MPI+X and a domain scientist may simply not be aware of models that are a good fit to their domain. Second, they are less mature than MPI+X and likely have more functionality or performance “potholes” that need only be identified to be addressed.
PAW-ATM is a forum for discussing HPC applications written in alternatives to MPI+X. Its goal is to bring together application experts and proponents of high-level languages to present concrete example uses of such alternatives, describing their benefits and challenges.
Scope and Aims
The PAW-ATM workshop is designed to be a forum for discussion of supercomputing-scale parallel applications and their implementation in programming models outside of the dominant MPI+X paradigm. Papers and talks will explore the benefits (or perhaps drawbacks) of implementing specific applications with alternatives to MPI+X, whether those benefits are in performance, scalability, productivity, or some other metric important to that application domain. Presenters are encouraged to generalize the experience with their application to other domains in science and engineering and to bring up specific areas of improvement for the model(s) used in the implementation.
In doing so, our hope is to create a setting in which application authors, language designers, and architects can present and discuss the state of the art in alternative scalable programming models, while also wrestling with how to increase their effectiveness and adoption. Beyond well-established HPC scientific simulations, we also encourage submissions exploring artificial intelligence, big data analytics, machine learning, and other emerging application areas.
Topics
Topics of interest include, but are not limited to:
Papers that include description of applications that demonstrate the use of alternative programming models will be given higher priority.
Submissions
Submissions are solicited in two tracks:
Full-length papers will be published in the workshop proceedings. Submitted papers must describe original work that has not appeared in, nor is under consideration for, another conference or journal. Papers shall be eight (8) pages minimum and not exceed ten (10) pages including text, figures, and non-AD appendices, but excluding bibliography and acknowledgments.
PAW-ATM follows the reproducibility initiative of SC24. Submissions shall include an Artifact Description (AD) appendix. The appendix pages related to the reproducibility initiative dependencies are not included in the page count.
Authors should include a draft of your AD/AE appendix with the initial manuscript pdf submission. You will have the opportunity to revise the appendix before its final submission on September 4, 2024.
Abstracts will be evaluated separately and will not be included in the published proceedings. Submissions in this track will include a title and a 1-page abstract and the content may include any combination of novel and/or previously published work that is relevant to the workshop's scope.
When deciding between manuscript submissions with similar merit, submissions whose focus relates more directly to the key themes of the workshop (application studies, computing at scale, high-level alternatives to MPI+X) will be given priority over those that don't.
Manuscripts shall be submitted through Linklings. Please use the IEEE conference proceeding templates.