AMRIC: A Novel in Situ Lossy Compression Framework for Efficient I/O in Adaptive Mesh Refinement Applications

Daoce Wang, Jesus Pulido, Pascal Grosset, Jiannan Tian, Sian Jin, Houjun Tang, Jean Sexton, Sheng Di, Kai Zhao, Bo Fang, Zarija Lukić, Franck Cappello, James Ahrens, Dingwen Tao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

As supercomputers advance towards exascale capabilities, computational intensity increases significantly, and the volume of data requiring storage and transmission experiences exponential growth. Adaptive Mesh Refinement (AMR) has emerged as an effective solution to address these two challenges. Concurrently, error-bounded lossy compression is recognized as one of the most efficient approaches to tackle the latter issue. Despite their respective advantages, few attempts have been made to investigate how AMR and error-bounded lossy compression can function together. To this end, this study presents a novel in-situ lossy compression framework that employs the HDF5 filter to improve both I/O costs and boost compression quality for AMR applications. We implement our solution into the AMReX framework and evaluate on two real-world AMR applications, Nyx and WarpX, on the Summit supercomputer. Experiments with 4096 CPU cores demonstrate that AMRIC improves the compression ratio by up to 81× and the I/O performance by up to 39× over AMReX's original compression solution.

Original languageEnglish (US)
Title of host publicationProceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2023
PublisherAssociation for Computing Machinery
ISBN (Electronic)9798400701092
DOIs
StatePublished - Nov 12 2023
Externally publishedYes
Event2023 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2023 - Denver, United States
Duration: Nov 12 2023Nov 17 2023

Publication series

NameProceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2023

Conference

Conference2023 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2023
Country/TerritoryUnited States
CityDenver
Period11/12/2311/17/23

Keywords

  • AMR
  • I/O
  • lossy compression
  • performance

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications

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