[hpc-announce] ESwML 2024 Call For Papers April 2024 ( Held in conjunction with EuroSys-24)

[Konstantinos Parasyris]

I apologize if you already received this CFP.

This is a CALL FOR PAPERS for

     ESwML 2024

1st International Workshop on
Empowering Software through Machine Learning

https://eswml.github.io

held in conjunction with EuroSys 2024 in Athens, Greece.

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IMPORTANT DATES:
Paper submission:     February 14, 2024 (AoE)
Author notification:  March 8, 2024
Camera Ready:           March 13 2024
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OVERVIEW:

The software of tomorrow will heavily rely
on the use of machine learning models. This
will span various aspects including using
Machine Learning (ML) models during the
development time to enhance developer
productivity, designing ML heuristics to improve
application execution, and adopting surrogate
Neural Networks (NN) models within applications
to replace expensive computations and
accelerate their performance. However, several
challenges limit the broad adoption of ML in today’s software.

For example, there are no programming language
extensions that can capture the developer’s intent
to use surrogate NN models in their applications,
nor can task scheduling algorithms communicate
seamlessly with ML heuristics to decide and schedule
tasks. As applications continue to get integrated into
complex, deep software stacks with workflows,
compilers, runtime libraries, and heterogeneous
systems, it becomes necessary to use novel techniques
for assisting software development, supporting
the application execution orchestration, and potentially
improving application performance.

The goal of Empowering Software through Machine
Learning (ESwML) workshop is to establish a platform
where researchers, scientists, application developers,
computing center staff, and industry professionals
can come together to exchange ideas and explore
how artificial intelligence can help in effective
and efficient use of future systems.

This workshop will actively drive discussion and aim to
answer the following questions:

How can we leverage the advances in
Machine Learning to ease the software
development process?
How can ML be applied to automate heuristic
design? These heuristics play a crucial role in:
compile-time performance prediction,
scheduling policies adopted by datacenters,
cloud communities, and HPC programming models.
How can we seamlessly integrate ML models
into applications to improve their performance
while ensuring the correctness of the generated outputs?


PAPER SUBMISSION:

Papers must be submitted electronically as PDF
files, formatted for 8.5x11-inch paper. The length
of the paper must be no more than 8 pages in the
ACM double-column format (10-pt font).
References are out of the 6 pages limit.
Short paper submissions, even with only 2 pages,
are welcome as well.

Submissions should use PDF format and
be printable on US Letter or A4 paper.
Please submit your manuscripts through hotcrp:

https://eswml24.hotcrp.com/

Proceedings will be posted online. If the final version of an accepted
paper does not sufficiently address the comments of the reviewers, then
it may be accompanied by a note from the program committee. Publication
at ESwML will not prevent later publication in conferences or journals
of the presented work. However, simultaneous submission to ESwML and
other workshop, conference, or journal is often prohibited by the policy
of other venues.

The presentation should take no longer than 25 minutes to present.
Please make sure that at least one of the authors can attend the
workshop if your work is accepted.

Organizers and Program Chairs:

Florina M. Ciorba, University of Basel
Parasyris, Konstantinos, Lawrence Livermore National Laboratory
William S. Moses, University of Illinois Urbana-Champaign
Gopalakrishnan Menon, Harshitha Lawrence Livermore National Laboratory