pdsw-DISCS 2018:

3RD Joint International Workshop on Parallel Data Storage & Data Intensive Scalable Computing Systems


HELD IN CONJUNCTION WITH SC18: THE INTERNATIONAL CONFERENCE FOR HIGH PERFORMANCE COMPUTING, NETWORKING, STORAGE & ANALYSIS

HELD IN COOPERATION WITH IEEE TCHPC


Monday, November 12, 2018

Kay Bailey Hutchison
Convention Center
DALLAS, TX

Time: 9:00am - 5:30 pm

Location: D163 (map)
SC Workshop page


Program Co-Chairs:

New York University


Amazon Web Services

Publicity Chair:

Lawrence Berkeley National Laboratory

Web & Publications Chair:

Carnegie Mellon University
General Chair:

Lawrence Livermore National Laboratory

Reproducibility Co-Chairs:

University of California, Santa Cruz


University of California, Santa Cruz

abstract / agenda / keynote speaker / cfp / submissions / WIP session / committees
author instructions

IMPORTANT DATES:
Work In Progress (WIP) Abstract Submissions due: Nov. 1, 2018, 11:59 PM AoE WIP Notification: Nov. 7, 2018


keynote speaker

PDSW-DISCS18 is proud to announce that Rangan Sukumar, Cray, will be our keynote speaker. Please watch for further details here.

Rangan Sukumar is an artificial intelligence researcher who architects productive and performant data solutions. He serves as the Senior Analytics Architect in the CTO’s office at Cray Inc. His role is three-fold: (i) Analytics evangelist - Demonstrating what Big Data and HPC can do for data-centric organizations, (ii) Technology visionary - Designing the roadmap for analytic products through evaluation of customer requirements and aligning them with emerging hardware and software technologies, (iii) Solutions architect - Creating bleeding-edge solutions for scientific and enterprise problems in the long-tail of the Big Data market requiring scale and performance beyond what cloud computing offers. Before his role at Cray, he served as the founding group leader, data scientist and artificial intelligence/machine learning researcher scaling algorithms on unique super-computing infrastructures at the Oak Ridge National Laboratory. He has over 70 publications in areas of disparate data collection, organization, processing, integration, fusion, analysis and inference - applied to a wide variety of domains such as healthcare, social network analysis, electric grid modernization and public policy informatics. As an entrepreneur at heart, he also serves on several technical advisory boards and committees for several startups.


agenda


Information on scheduling will be added here as the event approaches.


WORKSHOP ABSTRACT


(Find the complete proposal outlining the merger between PDSW and DISCS here.)

We are pleased to announce that the third Joint International Workshop on Parallel Data Storage and Data Intensive Scalable Computing Systems (PDSW-DISCS’18) will be hosted at SC18: The International Conference for High Performance Computing, Networking, Storage and Analysis. The objective of this one day joint workshop is to combine two overlapping communities and to better promote and stimulate researchers’ interactions to address some of the most critical challenges for scientific data storage, management, devices, and processing infrastructure for both traditional compute intensive simulations and data-intensive high performance computing solutions. Special attention will be given to issues in which community collaboration can be crucial for problem identification, workload capture, solution interoperability, standards with community buy-in, and shared tools.

Many scientific problem domains continue to be extremely data intensive. Traditional high performance computing (HPC) systems and the programming models for using them such as MPI were designed from a compute-centric perspective with an emphasis on achieving high floating point computation rates. But processing, memory, and storage technologies have not kept pace and there is a widening performance gap between computation and the data management infrastructure. Hence data management has become the performance bottleneck for a significant number of applications targeting HPC systems. Concurrently, there are increasing challenges in meeting the growing demand for analyzing experimental and observational data.

In many cases, this is leading new communities to look towards HPC platforms. In addition, the broader computing space has seen a revolution in new tools and frameworks to support Big Data analysis and machine learning. There is a growing need for convergence between these two worlds. Consequently, the U.S. Congressional Office of Management and Budget has informed the U.S. Department of Energy that new machines beyond the first exascale machines must address both the traditional simulation workloads as well as data intensive applications. This coming convergence prompted the integration of the PDSW and DISCS workshops into a single entity to address the common challenges.

The scope of the proposed joint PDSW-DISCS workshop is summarized as:

  • Scalable storage architectures, archival storage, storage virtualization, emerging storage devices and techniques
  • Performance benchmarking, resource management, and workload studies from production systems including both traditional HPC and data-intensive workloads.
  • Programmability, APIs, and fault tolerance of storage systems
  • Parallel file systems, metadata management, and complex data management, object and key-value storage, and other emerging data storage/retrieval techniques
  • Programming models and frameworks for data intensive computing including extensions to traditional and nontraditional programming models, asynchronous multi-task programming models, or to data intensive programming models
  • Techniques for data integrity, availability and reliability especially
  • Productivity tools for data intensive computing, data mining and knowledge discovery
  • Application or optimization of emerging “big data” frameworks towards scientific computing and analysis
  • Techniques and architectures to enable cloud and container-based models for scientific computing and analysis
  • Techniques for integrating compute into a complex memory and storage hierarchy facilitating in situ and in transit data processing
  • Data filtering/compressing/reduction techniques that maintain sufficient scientific validity for large scale compute-intensive workloads
  • Tools and techniques for managing data movement among compute and data intensive components both solely within the computational infrastructure as well as incorporating the memory/storage hierarchy

CALL FOR PAPERS

 

CALL FOR PAPERS POSTER - Download & hang one in your office!

This year, we are soliciting two categories of papers, regular papers and reproducibility study papers. Both 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 in the digital libraries of the IEEE and ACM.


Regular paper SUBMISSIONS

 

We invite regular papers which may optionally include Experimental Details Appendices as described here for SC. Submissions that include experimental appendices and/or reproducibility information for automated validation (described below) will be given special consideration by the Program Committee. Authors are encouraged to include reproducibility information for automated validation of experimental results. A description of the infrastructure available for automated validation and the criteria used in validation are available here. Accepted submissions passing automated validation will earn the Results Replicated badge in the ACM DL in accordance with ACM’s artifact evaluation policy.

Deadlines

Submissions deadline: Submissions closed
Submissions website: https://submissions.supercomputing.org/
Notification: September 30, 2018
Camera ready and copyright forms due: October 5, 2018
Slides due before workshop: Friday, November 9, 2018 to jdigney@cs.cmu.edu
* Submissions must be in the IEEE conference format


NEW! REPRODUCIBILITY STUDY PAPER SUBMISSIONS

We also call for reproducibility studies that for the first time reproduce experiments from papers previously published in PDSW-DISCS or in other peer-reviewed conferences with similar topics of interest (see reproducibility study instructions). Reproducibility study submissions are selected by the same peer-reviewed competitive process as regular papers, except these submissions must pass automated validation of experimental results (see artifact evaluation criteria). Accepted submissions passing automated validation will earn the prestigious ACM “Results Replicated” Badge and, if the work under study was successfully reproduced, the associated paper will earn the ACM “Results Reproduced” Badge in the ACM DL in accordance with ACM’s artifact review and badging policy.

DEADLINES

Submissions deadline: Submissions closed
Submissions website: https://submissions.supercomputing.org/
Notification: September 30, 2018
Camera ready and copyright forms due: October 5, 2018
Slides due before workshop: Friday, November 9, 2018 to jdigney@cs.cmu.edu
* Submissions must be in the IEEE conference format.

Details on reproducibility criteria are here.


Guidelines for Regular Papers and Reproducibility Study Papers

Submit a not previously published paper as a PDF file, indicate authors and affiliations. Papers must be at least 8 pages long and no more than 12 pages long (including appendices and references). Download the IEEE conference paper template.

Details on reproducibility criteria are here.


Work-in-progress (WIP) Submissions


There will be a WIP session where presenters provide brief 5-minute talks 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. A one-page abstract is required.

Please email your submission to:

WIP Submission Deadline: November 1, 2018
WIP Notification: November 7, 2018


ATTENDING THE WORKSHOP

Please be aware that all attendees to the workshop, both speakers and participants, will have to pay the SC18 registration fee. Workshops are no longer included as part of the technical program registration.

To attend the workshop, please register through the Supercomputing '18 registration page. Registration opens July 11, 2018.


PROGRAM COMMITTEE:

  • Suren Byna, Lawrence Berkeley National Laboratory
  • Shane Canon, Lawrence Berkeley National Laboratory
  • Yong Chen, Texas Tech University
  • Toni Cortes, Universitat Politècnica de Catalunya
  • Stratos Efstathiadis, NYU High Performance Computing
  • Elsa Gonsiorowski, Lawrence Livermore National Laboratory
  • Bingsheng He, National University of Singapore
  • Jian Huang, UIUC
  • Shadi Ibrahim, Inria
  • Dries Kimpe, KCG
  • Steve Leak, NERSC
  • Jay Lofstead, Sandia National Laboratories
  • Johann Lombardi, Intel
  • Xiaoyi Lu, The Ohio State University
  • Xiaosong Ma, Qatar Computing Research Institute
  • Sangmi Pallickara, Colorado State University
  • Rob Ross, Argonne National Laboratory
  • Philip C. Roth, Oak Ridge National Laboratory
  • Kento Sato, Lawrence Livermore National Laboratory

STEERING COMMITTEE:

  • John Bent, Cray
  • Ali R. Butt, Virginia Tech
  • Shane Canon, Lawrence Berkeley National Laboratory
  • Yong Chen, Texas Tech University
  • Evan J. Felix, Pacific Northwest National Laboratory
  • Gary Grider, Los Alamos National Laboratory
  • William D. Gropp, University of Illinois at Urbana-Champaign
  • Dean Hildebrand, Google
  • Dries Kimpe, KCG, USA
  • Jay Lofstead, Sandia National Laboratories
  • Xiaosong Ma, Qatar Computing Research Institute, Qatar
  • Carlos Maltzahn, University of California, Santa Cruz
  • Kathryn Mohror, Lawrence Livermore National Laboratory
  • Robert Ross, Argonne National Laboratory
  • Philip C. Roth, Oak Ridge National Laboratory
  • John Shalf, NERSC, Lawrence Berkeley National Laboratory
  • Xian-He Sun, Illinois Institute of Technology
  • Rajeev Thakur, Argonne National Laboratory
  • Lee Ward, Sandia National Laboratories
  • Brent Welch, Google