[IPDPS] IPDPS 2025 - Call for Papers
Francesco Silvestri
francesco.silvestri at unipd.it
Fri Sep 27 06:57:08 UTC 2024
IPDPS 2025 CALL FOR PAPERS
10 October Deadline
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IEEE IPDPS 2025
39th IEEE International Parallel &
Distributed Processing Symposium
June 3-7, 2025
Milan, Italy
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IPDPS 2025 CALL FOR PAPERS
Important Dates:
• Thursday, October 3, 2024- Abstracts due
• Thursday, October 10, 2024 – Papers due
To see the full Call for Papers, visit ipdps.org.
IPDPS 2025 NOW OPEN FOR SUBMISSIONS
Authors are invited to submit manuscripts that present novel and impactful
research in high performance computing (HPC) in parallel and distributed
processing. Works focusing on emerging technologies, interdisciplinary work
spanning multiple IPDPS focus areas, and novel open-source artifacts are
welcome. Topics of interest include but are not limited to the following
areas:
Algorithms:
This track focuses on algorithms for computational and data science in
parallel and distributed computing environments (including cloud, edge,
fog, distributed memory, and accelerator-based computing).
Applications:
This track focuses on real-world applications (combinatorial, scientific,
engineering, data analysis, and visualization) that use parallel and
distributed computing concepts.
Architecture:
This track focuses on existing and emerging architectures for high
performance computing,
Machine Learning and Artificial Intelligence (ML/AI):
This track focuses on all areas of ML/AI that are relevant to parallel and
distributed computing.
Measurements, Modeling, and Experiments:
This track focuses on experiments and performance-oriented studies in the
practice of parallel and distributed computing.
Programming Models, Compilers, and Runtime Systems:
This track covers topics ranging from the design of parallel programming
models and paradigms to languages and compilers supporting these models and
paradigms to runtime and middleware solutions.
System Software:
This track focuses on software that is close to the bare high performance
computing (HPC) hardware.
The conference will recognize exceptional contributions with a Best Paper
Award and a Best Open-Source Contribution Award.
Visit the website at ipdps.org to see the full Call for Papers including
details of
WHAT/WHERE TO SUBMIT,
a description of REVIEW OF MANUSCRIPTS,
the IMPORTANT DATES, and
a listing of the PROGRAM COMMITTEE.
2025 PROGRAM CHAIRS
Michela Becchi, North Carolina State University
Karen Devine, Sandia National Laboratories, ret.
2025 PROGRAM AREA CO-CHAIRS
Algorithms
Maxim Naumov (Meta)
Albert-Jan Yzelman (Huawei Technologies)
Applications
Sanjukta Bhowmick (University of North Texas)
Kara Peterson (Sandia National Laboratories)
Architectures
Amro Awad (University of Oxford)
Antonino Tumeo (Pacific Northwest National Laboratory)
Machine Learning and Artificial Intelligence
Prasanna Balaprakash (Oak Ridge National Laboratory)
Dong Li (University of California, Merced)
Measurement, Performance and Experiments
Alexandru Iosup (Vruje Universiteit Amsterdam)
Tanzima Islam (Texas State University)
Programming Models, Compilers, and Runtime Systems
Franck Cappello (Argonne National Laboratory)
Xipeng Shen (North Carolina State University)
System Software
Patrick Bridges (University of New Mexico)
Sarah Neuwirth (Johannes Gutenberg University Mainz)
IPDPS 2025 Venue: Politecnico di Milano
Politecnico di Milano is the largest technical university in Italy,
offering undergraduate, graduate, and higher education courses in
engineering, architecture, and design. Founded in 1863, it is one of the
oldest universities in Milan.
IPDPS 2025 Location: Milan, Italy
Milan, a metropolis in Italy's northern Lombardy region, is a global
capital of fashion and design. Home to the national stock exchange, it’s a
financial hub also known for its high-end restaurants and shops. The Gothic
Duomo di Milano cathedral and the Santa Maria delle Grazie convent, housing
Leonardo da Vinci’s mural “The Last Supper,” testify to centuries of art
and culture.
2025 GENERAL CO-CHAIRS
Marco D. Santambrogio, Politecnico di Milano, Italy
Ananth Kalyanaraman, Washington State University, USA
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Sponsored by IEEE Computer Society Technical Community on Parallel
Processing
In cooperation with
ACM SIGARCH,
IEEE Computer Society Technical Committee on Computer Architecture and
IEEE Computer Society Technical Committee on Distributed Processing
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