ESSA 2023: 4th International Workshop on Extreme-Scale Storage and Analysis
(Formerly HPS: International Workshop on High Performance Storage)
Held in conjunction with IPDPS 2023 - May, 2023, St. Petersburg, Florida USA
https://sites.google.com/view/essa-2023/
We are organizing the fourth edition of the International Workshop on High Performance Storage (HPS) held in conjunction with IPDPS in 2020 and 2021 under a renewed name: ESSA - the International Workshop on Extreme-Scale Storage and Analytics (ESSA). The workshop is renamed to enlarge the scope of the HPS workshop mainly focused on storage to also more explicitly reflect our intention to also include topics related to data processing and analytics.
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 and I/O support systems that take advantage of hierarchical storage layers. 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:
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.
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.
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.
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".
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, including:
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.)
The workshop will accept traditional research papers (8-10 pages) for in-depth topics and short papers (4-7 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.
Paper format: 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
Submission site: https://ssl.linklings.net/conferences/ipdps/
Abstract submission (optional) deadline: January 14, 2023 January 28, 2023
Paper submission deadline: January 21, 2023 February 4, 2023
Acceptance notification: February 21, 2023 March 2, 2023
Camera-ready deadline: March 7, 2023 March 15, 2023
Workshop date: May 15, 2023
Workshop Chairs
Kento Sato, RIKEN, Japan - Chair - kento.sato@riken.jp
Gabriel Antoniu, Inria, France - Co-Chair - gabriel.antoniu@inria.fr
Program Chairs
Weikuan Yu, Florida State University, USA - Chair - yuw@cs.fsu.edu
Sarah Neuwirth, Goethe University Frankfurt, Germany - Co-Chair - s.neuwirth@em.uni-frankfurt.de
Web & Publicity Chair
François Tessier, Inria, France - Chair - francois.tessier@inria.fr
Program Committee
Gabriel Antoniu, French Insitute for Research in Computer Science and Automation (INRIA), France
Jean Luca Bez, Lawrence Berkeley National Laboratory (LBNL), USA
Suren Byna, Lawrence Berkeley National Laboratory (LBNL), USA
Franck Cappello, Argonne National Laboratory (ANL), USA
Wei Der Chien, University of Edinburgh, Great Britain
Alexandru Costan, French Insitute for Research in Computer Science and Automation (INRIA), France
Hariharan Devarajan, Lawrence Livermore National Laboratory (LLNL), Illinois Institute of Technology, USA
Matthieu Dorier, Argonne National Laboratory (ANL), USA
Hideyuki Kawashima, Keio University, Tokio, Japan
Younjae Kim, Sogang University, South Korea
Christos Kozanitis, Foundation for Research and Technology - Hellas (FORTH), Greece
Jay Lofstead, Sandia National Laboratories, USA
Ricardo Macedo, INESC TEC, University of Minho, Portugal
Sarah Neuwirth, Goethe University Frankfurt, Germany
Hiroki Ohtsuji, Fujitsu Ltd, Japan
Arnab K. Paul, PITS Pilani, K.K. Goa Campus, India
Dana Petcu, West University of Timisoara, Romania
Michael Schoettner, Duesseldorf University, Germany
Chen Wang, Lawrence Livermore National Laboratory (LLNL), USA
For additional details, see web site: https://sites.google.com/view/essa-2023/