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PDSW 2022 : The 7th International Parallel Data Systems Workshop

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Link: http://www.pdsw.org
 
When Nov 14, 2022 - Nov 14, 2022
Where Dallas, Texas, USA
Submission Deadline Aug 20, 2022
Notification Due Sep 9, 2022
Final Version Due Sep 30, 2022
 

Call For Papers

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

Topics of interest include the following:
- Scalable architectures for distributed data storage, archival, and virtualization
- 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 tolerance
- 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 stores
- 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
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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: https://www.ieee.org/conferences/publishing/templates.html


Work-in-progress (WIP) Submissions
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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
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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
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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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