ESSA 2023 : 4th Workshop on Extreme-Scale Storage and Analysis
Held in conjunction with IEEE IPDPS 2023 - May 15, 2023
Program
ATTENTION: The room for the ESSA Workshop has been changed to Skyway!
13:45 - 14:00 Welcome Message
14:00 - 15:00 Keynote: Perspectives on Provisioning and Supporting AI/ML and I/O on Leadership Computing Systems
— Feiyi Wang (Oak Ridge National Laboratory)
15:00 - 15:30 Coffee Break
15:30 - 15:50 Short Talk: Persistent Memory-Aware Scheduling for Serverless Workloads
— Samanta, Ahmed, Cao, Stutsman, Sharma
15:50 - 16:20 Paper Talk: HEPnOS: a Specialized Data Service for High Energy Physics Analysis
— Ali, Calvez, Carns, Dorier, Ding, Kowalkowski, Latham, Norman, Paterno, Ross, Sehrish, Snyder, Soumagne
16:20 - 16:40 Short Talk: An Empirical Roofline Model for Extreme-Scale I/O Workload Analysis
— Zhu, Bartelheimer, Neuwirth
16:40 - 17:10 Paper Talk: Efficient Asynchronous I/O with Request Merging
— Chowdhury, Tang, Bez, Byna, Bangalore
17:10 - 17:30 Closing Remarks
Keynote
Feiyi Wang (Oak Ridge National Laboratory)
Feiyi Wang received his Ph.D. in Computer Engineering from North Carolina State University (NCSU). He is the Group Leader of Analytics and AI methods at Scale Group (AAIMS), at National Center for Computational Sciences of Oak Ridge National Laboratory (ORNL). His research interests include large-scale data analytics, distributed machine learning and benchmarking, high performance storage system, parallel I/O and file systems. He is the recipient of SC'21 Best Paper Award, Bench'21 Best Paper Award, SC'21 and SC'22 Gordon Bell Covid Special Finalist, HPCC'17 Best Paper Finalist, SBDAC-PAD'16 Best Paper Finalist, SC'14 Best Paper Finalist. In 2022, He won UT-Battelle Award on Research Accomplishment, Distinguished Innovation, and prestigious Director's Award.
Dr. Wang held Joint Faculty Professor of ECE Department, Bredesen Center Faculty position at University of Tennessee. He is also a Senior Member of IEEE.
Workshop Overview
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 storage systems and I/O support software for several reasons:
Technology: The availability of an increasing number of persistent solid-state storage 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 can best be used to achieve the needed performance, so new approaches for using solid-state storage 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.
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 a “continuum” of computing.
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 including storage, I/O, processing and analysis on extreme scale infrastructures including HPC systems, clouds, edge systems or hybrid combinations of those, to discuss advances and possible solutions to the new challenges we face.
Topics
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 library and services
I/O performance in extreme-scale systems and applications (HPC/cloud/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.)
Chairs
Workshop Chairs
Chair: Kento Sato, RIKEN, Japan
Co-Chair: Gabriel Antoniu, Inria, France
Program Chairs
Chair: Weikuan Yu, Florida State University, USA
Co-Chair: Sarah Neuwirth, Goethe University Frankfurt, Germany
Web & Publicity Chair
Chair: François Tessier, Inria, France
Steering Committee
Gabriel Antoniu , Inria, Rennes, France
Franck Cappello, Argonne National Laboratory, USA
Toni Cortés, Barcelona Supercomputing Center, Spain
Kathryn Mohror, Lawrence Livermore National Laboratory, USA
Kento Sato, RIKEN, Japan
Marc Snir, University of Illinois at Urbana-Champaign, USA
Weikuan Yu, Florida State University, USA