[hpc-announce] [CFP] PDSW at SC22 - Papers due August 13, 2022

Jean Luca Bez jlbez at lbl.gov
Fri Jun 3 00:42:17 CDT 2022

                              Call for papers: PDSW’22
                The 7th International Parallel Data Systems Workshop
                      November 14, 2022  1:30 PM - 5:00 PM (CST)
                      Held in conjunction with SC22, DALLAS, TX
                      In cooperation with: IEEE Computer Society

We are pleased to announce the 7th International Parallel Data Systems
Workshop (PDSW’22). PDSW'22 will be hosted in conjunction with SC22: The
International Conference for High Performance Computing, Networking,
Storage and Analysis.

Efficient data storage and data management are crucial to scientific
productivity in both traditional simulation-oriented HPC environments and
Big Data analysis environments. This issue is further exacerbated by the
growing volume of experimental and observational data, the widening gap
between the performance of computational hardware and storage hardware, and
the emergence of new data-driven algorithms in machine learning. The goal
of this workshop is to facilitate research that addresses the most critical
challenges in scientific data storage and data processing. PDSW will
continue to build on the successful tradition established by its
predecessor workshops: the Petascale Data Storage Workshop (PDSW,
2006-2015) and the Data Intensive Scalable Computing Systems (DISCS
2012-2015) workshop. These workshops were successfully combined in 2016,
and the resulting joint workshop has attracted up to 38 full paper
submissions and 140 attendees per year from 2016 to 2021.

We encourage the community to submit original manuscripts that:

   - introduce and evaluate novel algorithms or architectures,
   - inform the community of important scientific case studies or
   workloads, or
   - validate the reproducibility of previously published work

Special attention will be given to issues in which community collaboration
is crucial for problem identification, workload capture, solution
interoperability, standardization, and shared tools.  We also strongly
encourage papers to share complete experimental environment information
(software version numbers, benchmark configurations, etc.) to facilitate

Topics of interest include the following:

   - Scalable architectures for distributed data storage, archival, and
   - The application of new data processing models and algorithms towards
   scientific computing and analysis
   - Performance benchmarking, resource management, and workload studies
   - Enabling cloud and container-based models for scientific data analysis
   - Techniques for data integrity, availability, reliability, and fault
   - Programming models and big data frameworks for data intensive computing
   - Hybrid cloud/on-premise data processing
   - Cloud-specific data storage and transit costs and opportunities
   - Programmability of storage systems
   - Data filtering/compressing/reduction techniques
   - Parallel file systems, metadata management, and complex data management
   - Integrating computation into the memory and storage hierarchy to
   facilitate in-situ and in-transit data processing
   - Alternative data storage models, including object stores and key-value
   - Productivity tools for data intensive computing, data mining, and
   knowledge discovery
   - Tools and techniques for managing data movement among compute and data
   intensive components
   - Cross-cloud data management
   - Storage system optimization and data analytics with machine learning
   - Innovative techniques and performance evaluation for new memory and
   storage systems

Regular Paper Submissions
All papers will be evaluated by a competitive peer-review process under the
supervision of the workshop program committee. Selected papers and
associated talk slides will be made available on the workshop web site. The
papers will also be published by the IEEE Computer Society.

Authors of regular papers are strongly encouraged to submit Artifact
Description (AD) Appendices that can help to reproduce and validate their
experimental results. While the inclusion of the AD Appendices is optional
for PDSW’22, submissions that are accompanied by AD Appendices will be
given favorable consideration for the PDSW Best Paper award.

PDSW’22 follows the SC22 Reproducibility Initiative. For Artifact
Description (AD) Appendices, we will use the format of the SC22 for PDSW'22
submissions. The AD should include a field for one or more links to data
(zenodo, figshare, etc.) and code (github, gitlab, bitbucket, etc.)
repositories. For the Artifacts that will be placed in the code repository,
we encourage authors to follow the guidelines of SC22 on how to structure
the artifact, as it will make it easier to the reviewing committee and
readers of the paper in the future.

Submit a not previously published paper as a PDF file, indicate authors and
affiliations. Papers must be up to 5 pages, not less than 10 point font and
not including references and optional reproducibility appendices. Papers
must use the IEEE conference paper template available at:

Submission site: https://submissions.supercomputing.org

Work-in-progress (WIP) Submissions
There will be a WIP session where presenters provide brief 5-minute talks
(TBD) on their on-going work, with fresh problems/solutions. WIP content is
typically material that may not be mature or complete enough for a full
paper submission and will not be included in the proceedings. A one-page
abstract is required.

Important Dates
Regular Papers and Reproducibility Study Papers:
Submissions due: Aug. 13, 2022, 11:59 PM AoE
Paper Notification:   Sep. 9, 2022
Camera ready due:  Sep. 30, 2022, 11:59 PM AoE

Work in Progress (WIP):
Submissions due:  Sep. 16, 2022, 11:59PM AoE
WIP Notification:  On or before Sep. 23, 2022

Workshop Organizers
General Chair
- Kento Sato, RIKEN R-CCS, Japan

Program Co-Chairs
- Amelie Chi Zhou, Shenzhen University, China
- Bing Xie, Oak Ridge National Laboratory, USA

Publicity Chair
- Jean Luca Bez, Lawrence Berkeley National Laboratory, USA

Web and Proceedings Chair
- Joan Digney, Carnegie Mellon University

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