[hpc-announce] Fwd: CFP First Workshop on AI Assisted Software Development for HPC (AI4DEV) November 2023 ( Held in conjunction with SC-23 )

[Konstantinos Parasyris]

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First Workshop on AI-Assisted Software Development for HPC (AI4DEV)
November 2023, Denver, Colorado, USA, Held in conjunction with SC23
                              https://ai4dev-workshop.github.io/2023/
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Scientific software is an important component in the pursuit of
scientific discovery, software development in HPC continues to be
challenging. The software development process today combines
contributions from domain scientists, applied mathematicians, computer
scientists, and involves complex programming models. As a result of
these diverse contributions, software environments have become
significantly complicated.

With this increasing diversity, the complexity of software development
increases and it requires a steep learning curve for new developers,
resulting in a slower pace of software development. With the
continuous integration of scientific applications in complex, deep
software stacks (workflows, compilers, runtime libraries,
heterogeneous systems) novel techniques and practical tools for
assisting the software development in HPC are invaluable. Recent
advances in generative AI and large language models, such as GitHub’s
Copilot and OpenAI’s GPT, demonstrate interesting potential for
developer assistance and automated code synthesis.

The goal of the AI-Assisted Software Development for HPC (AI4DEV)
workshop is to create a forum composed of researchers, scientists,
application developers, computing center staff, and industry staff to
discuss ideas on how artificial intelligence can help in the whole
development process. The workshop will feature contributed papers and
invited talks in the area.

Workshop TopicsTopics of interest include, but are not limited to:
* Machine learning techniques to improve programming productivity
* Performance analysis driven by AI and ML
* Debugging and testing driven by ML/AI
* ML-assisted compiler optimizations and code generation
* Auto-tuning and performance portability using ML/AI
*  Code synthesis and generation using automated ML techniques
* AI-assisted code recommendations for code maintainability,
performance and correctness
* IDE extensions using ML for improved programming productivity
* AI-assisted software building and deployment
* Mining best programming practices using ML
* Addressing security, privacy, and licensing concerns using ML/AI for
software development

Important Dates
Paper submissions due: August 7th, 2023
Notification of acceptance: September 4th, 2023
E-copyright registration completed by authors: September 13th, 2023
Camera-ready papers due: October 2023

Workshop Program Committee
* Alfredo Goldman, University of São Paulo
* Jan Hückelheim, Argonne National Laboratory
* Nikhil Jain, NVIDIA
* Tarindu Jayatilaka, Purdue University
* Dong Li, University of California, Merced
* Chunhua Liao, Lawrence Livermore National Laboratory
* Harshitha Menon, Lawrence Livermore National Laboratory
* Dejan Milojici, Hewlett Packard Labs
* William S. Moses, Massachusetts Institute of Technology
* Boyanna Norris, University of Oregon
* EunJung (EJ) Park, Qualcomm Inc.
* Pavlos Petoumenos, University of Manchester
* Kento Sato, RIKEN
* Keren Zhou, Rice University

The organizers,
* Giorgis Georgakoudis, Lawrence Livermore National Laboratory
* Ignacio Laguna, Lawrence Livermore National Laboratory
* Konstantinos Parasyris, Lawrence Livermore National Laboratory