Design and Implementation of Papyrus: Parallel Aggregate Persistent Storage

Jungwon Kim, Kittisak Sajjapongse, Seyong Lee, Jeffrey S. Vetter

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

A surprising development in recently announced HPC platforms is the addition of, sometimes massive amounts of, persistent (nonvolatile) memory (NVM) in order to increase memory capacity and compensate for plateauing I/O capabilities. However, there are no portable and scalable programming interfaces using aggregate NVM effectively. This paper introduces Papyrus: A new software system built to exploit emerging capability of NVM in HPC architectures. Papyrus (or Parallel Aggregate Persistent-YRU-Storage) is a novel programming system that provides features for scalable, aggregate, persistent memory in an extreme-scale system for typical HPC usage scenarios. Papyrus mainly consists of Papyrus Virtual File System (VFS) and Papyrus Template Container Library (TCL). Papyrus VFS provides a uniform aggregate NVM storage image across diverse NVM architectures. It enables Papyrus TCL to provide a portable and scalable high-level container programming interface whose data elements are distributed across multiple NVM nodes without requiring the user to handle complex communication, synchronization, replication, and consistency model. We evaluate Papyrus on two HPC systems, including UTK Beacon and NERSC Cori, using real NVM storage devices.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium, IPDPS 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1151-1162
Number of pages12
ISBN (Electronic)9781538639146
DOIs
StatePublished - Jun 30 2017
Event31st IEEE International Parallel and Distributed Processing Symposium, IPDPS 2017 - Orlando, United States
Duration: May 29 2017Jun 2 2017

Publication series

NameProceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium, IPDPS 2017

Conference

Conference31st IEEE International Parallel and Distributed Processing Symposium, IPDPS 2017
Country/TerritoryUnited States
CityOrlando
Period05/29/1706/2/17

Funding

This material is based upon work supported by the National Science Foundation under Grant Number 1137097 and by the University of Tennessee through the Beacon Project. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation or the University of Tennessee. This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research. This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan.

FundersFunder number
National Science Foundation1137097
U.S. Department of EnergyDE-AC02-05CH11231
New York Public Library
Office of Science
Advanced Scientific Computing Research
University of Tennessee
CelgardDE-AC05-00OR22725

    Keywords

    • Nonvolatile memory
    • distributed systems
    • persistent memory
    • programming systems

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