[IPDPS] [CFP - Reminder] ESSA Workshop at IEEE IPDPS 2024 - Submissions due January 25, 2024

Fri Dec 29 15:26:11 UTC 2023

**[Apologies if you receive multiple copies of this email]**

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Call for Papers

ESSA 2024: The 5th Workshop on Extreme-Scale Storage and Analysis
(Formerly High Performance Storage (HPS))

Held in conjunction with IEEE IPDPS 2024, San Francisco, CA, USA.

Workshop Date: May 2024

(https://sites.google.com/view/essa-2024)

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We are organizing the fifth edition of the International Workshop on 
Extreme-Scale Storage and Analytics (ESSA) held in conjunction with 
IPDPS since 2020 (formerly High Performance Storage (HPS) in 2020 and 
2021). Advances in storage are becoming increasingly critical because 
workloads on high performance computing (HPC) and cloud systems are 
producing and consuming more data than ever before, and the situation 
promises to only increase in future years. Additionally, the last 
decades have seen relatively few changes in the structure of parallel 
file systems, and limited interaction between the evolution of parallel 
file systems, e.g., Lustre, GPFS, and I/O support systems that take 
advantage of hierarchical storage layers, e.g., node local burst 
buffers. However, recently the community has seen a large uptick in 
innovations in data storage and processing systems as well as in I/O 
support software for several reasons:

(1) Technology: The availability of an increasing number of persistent 
solid-state storage and persistent storage-class memory technologies 
that can replace either memory or disk are creating new opportunities 
for the structure of storage systems.

(2) Performance requirements: Disk-based parallel file systems cannot 
satisfy the performance needs of high-end systems. However, it is not 
clear how solid-state storage and storage-class memory can best be used 
to achieve the needed performance, so new approaches for using 
solid-state storage and storage-class memory in HPC systems are being 
designed and evaluated.

(3) Application evolution: Data analysis applications, including graph 
analytics and machine learning, are becoming increasingly important both 
for scientific computing and for commercial computing.  I/O is often a 
major bottleneck for such applications, both in cloud and HPC 
environments – especially when fast turnaround or integration of heavy 
computation and analysis are required. Consequently, data storage, I/O 
and processing requirements are evolving, as complex workflows involving 
computation, analytics and learning emerge.

(4) Infrastructure evolution: HPC technology will not only be deployed 
in dedicated supercomputing centers in the future. “Embedded HPC”, “HPC 
in the box”, “HPC in the loop”, “HPC in the cloud”, “HPC as a service”, 
and “near-to-real-time simulation” are concepts requiring new 
small-scale deployment environments for HPC. A federation of systems and 
functions with consistent mechanisms for managing I/O, storage, and data 
processing across all participating systems will be required to create 
what is called a “computing continuum”.

(5) Virtualization and disaggregation: As virtualization and 
disaggregation become broadly used in cloud and HPC computing, the issue 
of virtualized storage has increasing importance and efforts will be 
needed to understand its implications for performance.

Our goals in the ESSA Workshop are to bring together expert researchers 
and developers in data-related areas such as storage, I/O, processing 
and analytics on extreme scale infrastructures including HPC systems, 
clouds, edge systems or hybrid combinations of these, to discuss 
advances and possible solutions to the new challenges we face. We expect 
the ESSA Workshop to result in lively interactions over a wide range of 
interesting topics.

Topics of interest include, but are not limited to:
  - Extreme-scale storage systems (on high-end HPC infrastructures, 
clouds, or hybrid combinations of them)
  - Extreme-scale parallel and distributed storage architectures
  - The synergy between different storage models (POSIX file system, 
object storage, key-value, row-oriented, and column-oriented databases)
  - Structures and interfaces for leveraging persistent solid-state 
storage and storage-class memory
  - High-performance I/O libraries and services
  - I/O performance in extreme-scale systems and applications 
(HPC/clouds/edge)
  - Storage and data processing architectures and systems for hybrid 
HPC/cloud/edge infrastructures, in support of complex workflows 
potentially combining simulation and analytics
  - Integrating computation into the memory and storage hierarchy to 
facilitate in-situ and in-transit data processing
  - I/O characterization and data processing techniques for application 
workloads relying on extreme-scale parallel/distributed 
machine-learning/deep learning
  - Tools and techniques for managing data movement among compute and 
data intensive components
  - Data reduction and compression
  - Failure and recovery of extreme-scale storage systems
  - Benchmarks and performance tools for extreme-scale I/O
  - Language and library support for data-centric computing
  - Storage virtualization and disaggregation
  - Ephemeral storage media and consistency optimizations
  - Storage architectures and systems for scalable stream-based processing
  - Study cases of I/O services and data processing architectures in 
support of various application domains (bioinformatics, scientific 
simulations, large observatories, experimental facilities, etc.)

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Submission Guidelines
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The workshop will accept traditional research papers (Page limit: 8 
pages) for in-depth topics and short papers (Page limit: 5 pages) for 
work in progress on hot topics. Papers should present original research 
and provide sufficient background material to make them accessible to 
the broader community. Papers with 5 pages or less are reviewed as 
Short/work-in-progress papers. Short papers must have 4 pages to be 
published in the IEEE Digital Library.

Formatting:
Single-spaced double-column pages using 10-point size font on 8.5x11 
inch pages (IEEE conference style), including figures, tables, and 
references. The submitted manuscripts should include author names and 
affiliations. The IEEE conference style templates for MS Word and LaTeX 
provided by IEEE eXpress Conference Publishing are available here: 
https://www.ieee.org/conferences/publishing/templates.html .
All papers must be in English. We use single-blind reviewing process, so 
please keep the authors names, publications, etc., in the text. Papers 
will be peer-reviewed, and accepted papers will be published in the 
workshop proceedings as part of the IEEE Digital Library.

Submission link (login required, opening soon):
https://ssl.linklings.net/conferences/ipdps/?page=Submit&id=ESSAWorkshopFullSubmission&site=ipdps2024

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Important Dates
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Please note: All deadlines are midnight Anywhere on Earth
- Abstract submission (optional) deadline: January 18, 2024
- Paper submission deadline: January 25, 2024
- Acceptance notification: February 15, 2024
- Camera-ready deadline: February 29, 2024
- Workshop date: May 2024 (day TBA)

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Workshop Committees
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Workshop Chairs:
- Chair: François Tessier, Inria, France
- Co-Chair: Weikuan Yu, Florida State University, USA

Program Chairs:
- Chair: Sarah Neuwirth, Johannes Gutenberg University Mainz, Germany
- Co-Chair: Arnab K. Paul, BITS Pilani, K K Birla Goa Campus, India

Web Chair:
- Chair: Lenny Guo, Pacific Northwest National Laboratory, Richmond, USA

Publicity Chair:
- Chair: Chen Wang, Lawrence Livermore National Laboratory, Livermore, USA

Steering Committee:
- Gabriel Antoniu , INRIA Rennes
- Franck Cappello, Argonne National Laboratory
- Tony Cortes, Barcelona Supercomputing Center
- Kathryn Mohror, Lawrence Livermore National Laboratory
- Kento Sato, RIKEN
- Marc Snir, University of Illinois at Urbana-Champaign
- Weikuan Yu, Florida State University

Program Committee:
- Tyler Allen, University of North Carolina at Charlotte, USA
- Oceane Bel, Pacific Northwest National Laboratory (PNNL), USA
- Sajal Dash, Oak Ridge National Laboratory (ORNL), USA
- Matthieu Dorier, Argonne National Laboratory (ANL), USA
- Anna Fuchs, University of Hamburg, Germany
- Hariharan Devarajan, Lawrence Livermore National Laboratory (LLNL), USA
- Adrian Jackson, The University of Edinburgh, UK
- Hideyuki Kawashima, Keio University, Japan
- Radita Liem, RWTH Aachen University, Germany
- Glenn K. Lockwood, Microsoft, USA
- Xiaoyi Lu, University of California Merced, USA
- Osamu Tatebe, University of Tsukuba, Japan
- Luan Teylo, 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
- Dongfang Zhao, University of Washington, USA

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Prof. Dr. Sarah M. Neuwirth
Johannes Gutenberg University Mainz
High Performance Computing and its Applications
Anselm-Franz-von-Bentzelweg 12
55099 Mainz | Germany
Phone: +49 6131 39 23643
Email: neuwirth at uni-mainz.de
Website: https://www.hpca-group.de/
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