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Particle tracking in open simulation laboratories

Published: 15 November 2015 Publication History

Abstract

Particle tracking along streamlines and pathlines is a common scientific analysis technique, which has demanding data, computation and communication requirements. It has been studied in the context of high-performance computing due to the difficulty in its efficient parallelization and its high demands on communication and computational load. In this paper, we study efficient evaluation methods for particle tracking in open simulation laboratories. Simulation laboratories have a fundamentally different architecture from today's supercomputers and provide publicly-available analysis functionality. We focus on the I/O demands of particle tracking for numerical simulation datasets 100s of TBs in size. We compare data-parallel and task-parallel approaches for the advection of particles and show scalability results on data-intensive workloads from a live production environment. We have developed particle tracking capabilities for the Johns Hopkins Turbulence Databases, which store computational fluid dynamics simulation data, including forced isotropic turbulence, magnetohydrodynamics, channel flow turbulence and homogeneous buoyancy-driven turbulence.

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cover image ACM Conferences
SC '15: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis
November 2015
985 pages
ISBN:9781450337236
DOI:10.1145/2807591
  • General Chair:
  • Jackie Kern,
  • Program Chair:
  • Jeffrey S. Vetter
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 15 November 2015

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Author Tags

  1. data-intensive computing
  2. particle tracking
  3. scientific databases
  4. turbulence

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SC '15 Paper Acceptance Rate 79 of 358 submissions, 22%;
Overall Acceptance Rate 1,516 of 6,373 submissions, 24%

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