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Call for Papers
REX-IO 2023: 3rd Workshop on Re-envisioning Extreme-Scale I/O for
Emerging Hybrid HPC Workloads
Held in conjunction with IEEE Cluster 2023, Santa Fe, NM, USA.
Workshop Date: October 31, 2023
(https://sites.google.com/view/rexio/)
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Scope, Aims, and Topics
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High Performance Computing (HPC) applications are evolving to include
not only traditional modeling and simulation bulk-synchronous scale-up
workloads but also scale-out workloads, including artificial
intelligence (AI), big data analytics methods, deep learning, and
complex multi-step workflows. With the advent of Exascale systems such
as Frontier, workflows include multiple different components from both
scale-up and scale-out communities operating together to drive
scientific discovery and innovation. With the often conflicting design
choices between optimizing for write- vs. read-intensive, having
flexible I/O systems is crucial to support hybrid workloads. Another
performance aspect is the intensifying complexity of parallel file and
storage systems in large-scale cluster environments. Storage system
designs are advancing beyond the traditional two-tiered file system and
archive model by introducing new tiers of temporary, fast storage close
to the computing resources with distinctly different performance
characteristics.
The changing landscape of emerging hybrid HPC workloads along with the
ever increasing gap between the compute and storage performance
capabilities reinforces the need for an in-depth understanding of
extreme-scale I/O and for rethinking existing data storage and
management techniques. Traditional approaches of managing data might
fail to address the challenges of extreme-scale hybrid workloads. Novel
I/O optimization and management techniques integrating machine learning
and AI algorithms, such as intelligent load balancing and I/O pattern
prediction, are needed to ease the handling of the exponential growth of
data as well as the complex hierarchies in the storage and file systems.
Furthermore, user-friendly, transparent and innovative approaches are
essential to adapt to the needs of different HPC I/O workloads while
easing the scientific and commercial code development and efficiently
utilizing extreme-scale parallel I/O and storage resources.
Established at IEEE Cluster 2021, the Re-envisioning Extreme-Scale I/O
for Emerging Hybrid HPC Workloads (REX-IO) workshop has created a forum
for experts, researchers, and engineers in the parallel I/O and storage,
compute facility operation, and HPC application domains. REX-IO solicits
novel work that characterizes I/O behavior and identifies the challenges
in scientific data and storage management for emerging HPC workloads,
introduces potential solutions to alleviate some of these challenges,
and demonstrates the effectiveness of the proposed solutions to improve
I/O performance for the exascale supercomputing era and beyond. We
envision that this workshop will contribute to the community and further
drive discussions between storage and I/O researchers, HPC application
users and the data analytics community to give a better in-depth
understanding of the impact on the storage and file systems induced by
emerging HPC applications.
Topics of interest include, but are not limited to:
- Understanding I/O inefficiencies in emerging workloads such as complex
multi-step workflows, in-situ analysis, AI, and data analytics methods
- New I/O optimization techniques, including how ML and AI algorithms
might be adapted for intelligent load balancing and I/O pattern
prediction of complex, hybrid application workloads
- Performance benchmarking and modeling, and I/O behavior studies of
emerging workloads
- New possibilities for the I/O optimization of emerging application
workloads and their I/O subsystems
- Efficient monitoring tools for metadata and storage hardware
statistics at runtime, dynamic storage resource management, and I/O load
balancing
- Parallel file systems, metadata management, and complex data management
- Understanding and efficiently utilizing complex storage hierarchies
beyond the traditional two-tiered file system and archive model
- User-friendly tools and techniques for managing data movement among
compute and storage nodes
- Use of staging areas, such as burst buffers or other private or shared
acceleration tiers for managing intermediate data between computation tasks
- Application of emerging big data frameworks towards scientific
computing and analysis
- Alternative data storage models, including object and key-value
stores, and scalable software architectures for data storage and archive
- Position papers on related topics
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Submission Guidelines
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All papers must be original and not simultaneously submitted to another
journal or conference. Indicate all authors and affiliations. All papers
will be peer-reviewed using a single-blind peer-review process by at
least three members of the program committee. Submissions should be a
complete manuscript. Full paper submissions should not exceed 6
single-spaced, double-column pages using 10-point size font on 8.5 X 11
inch pages (IEEE conference style,
https://www.ieee.org/conferences/publishing/templates.html) including
everything excluding references.
Papers are to be submitted electronically in PDF format through
EasyChair. Submitted papers should not have appeared in or be under
consideration for a different workshop, conference or journal. It is
also expected that all accepted papers will be presented at the workshop
by one of the authors.
All accepted papers (subject to post-review revisions) will be published
in the IEEE Cluster 2023 proceedings.
Submission Link: https://easychair.org/conferences/?conf=rexio23
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Important Dates
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Please note: All deadlines and dates are Anywhere on Earth
- Submissions open: May 26, 2023
- Submission deadline: August 15, 2023, 11:59PM AoE
- Notification to authors: September 4, 2023
- Camera-ready paper due: September 11, 2023
- Workshop date: October 31, 2023
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Workshop Committees
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Workshop Co-Chairs:
- Arnab K. Paul (BITS Pilani, K K Birla Goa Campus, India)
- Sarah M. Neuwirth (Goethe University Frankfurt, Germany)
- Jay Lofstead (Sandia National Laboratories, USA)
Program Committee:
- Phil Carns (Argonne National Laboratory, USA)
- Wei Der Chien (The University of Edinburgh, UK)
- Hariharan Devarajan (Lawrence Livermore National Laboratory, USA)
- Shadi Ibrahim (National Institute for Research in Digital Science and
Technology (Inria), France)
- Radita Liem (RWTH Aachen, Germany)
- Glenn Lockwood (Microsoft, USA)
- Ricardo Macedo (INESC TEC & University of Minho, Portugal)
- Preeti Malakar (Indian Institute of Technology Kanpur, India)
- Sebastian Oeste (TU Dresden, Germany)
- Kento Sato (RIKEN, Japan)
- Houjun Tang (Lawrence Berkeley National Laboratory, USA)
- François Tessier (National Institute for Research in Digital Science
and Technology (Inria), France)
- Marc-André Vef (Johannes Gutenberg University Mainz, Germany)
- Lipeng Wan (Georgia State University, USA)
- Chen Wang (Lawrence Livermore National Laboratory, USA)
- Mai Zheng (Iowa State University, USA)
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Contact
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All questions about submissions should be emailed to <rexio23 AT
easychair DOT org>
--
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Dr. Sarah M. Neuwirth
Goethe University Frankfurt | Campus Bockenheim
Modular Supercomputing and Quantum Computing
Kettenhofweg 139 | Room 102
60325 Frankfurt am Main | Germany
Phone: +49 (0)69 798-25256
Email: s.neuwirth@em.uni-frankfurt.de
Website: https://www.msqc.group/
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