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Title: Large-scale compute-intensive analysis via a combined in-situ and co-scheduling workflow approach, In: SC '15 Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis

Abstract

Large-scale simulations can produce hundreds of terabytes to petabytes of data, complicating and limiting the efficiency of workflows. Traditionally, outputs are stored on the file system and analyzed in post-processing. With the rapidly increasing size and complexity of simulations, this approach faces an uncertain future. Trending techniques consist of performing the analysis in-situ, utilizing the same resources as the simulation, and/or off-loading subsets of the data to a compute-intensive analysis system. We introduce an analysis framework developed for HACC, a cosmological N-body code, that uses both in-situ and co-scheduling approaches for handling petabyte-scale outputs. We compare different analysis set-ups ranging from purely off-line, to purely in-situ to in-situ/co-scheduling. The analysis routines are implemented using the PISTON/VTK-m framework, allowing a single implementation of an algorithm that simultaneously targets a variety of GPU, multi-core, and many-core architectures.

Authors:
 [1];  [2];  [3];  [1];  [4];  [5];  [6];  [7];  [1];  [4];  [8];  [1]
  1. Los Alamos National Lab, Los Alamos, NM
  2. OLCF, Oak Ridge National Lab, Oak Ridge, TN
  3. High Energy Physics, Argonne National Lab, Lemont, IL
  4. Argonne National Lab, Lemont, IL
  5. ALCF, Argonne National Lab, Lemont, IL
  6. Lawrence Livermore Nat. Lab, Livermore, CA
  7. OLCF Oak Ridge National Lab, Oak Ridge, TN
  8. University of Chicago and Argonne National Laboratory
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1567400
Resource Type:
Conference
Journal Name:
PROCEEDINGS OF SC15: THE INTERNATIONAL CONFERENCE FOR HIGH PERFORMANCE COMPUTING, NETWORKING, STORAGE AND ANALYSIS
Additional Journal Information:
Conference: International Conference for High Performance Computing, Networking, Storage and Analysis, Austin, Texas, November 15-20, 2015
Country of Publication:
United States
Language:
English
Subject:
Computer Science; Engineering

Citation Formats

Sewell, Christopher, Messer, Bronson, Habib, Salman, Ahrens, James, Heitmann, Katrin, Finkel, Hal, Zagaris, George, Parete-Koon, Suzanne T., Fasel, Patricia K., Pope, Adrian, Frontiere, Nicholas, and Lo, Li-ta. Large-scale compute-intensive analysis via a combined in-situ and co-scheduling workflow approach, In: SC '15 Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis. United States: N. p., 2015. Web. doi:10.1145/2807591.2807663.
Sewell, Christopher, Messer, Bronson, Habib, Salman, Ahrens, James, Heitmann, Katrin, Finkel, Hal, Zagaris, George, Parete-Koon, Suzanne T., Fasel, Patricia K., Pope, Adrian, Frontiere, Nicholas, & Lo, Li-ta. Large-scale compute-intensive analysis via a combined in-situ and co-scheduling workflow approach, In: SC '15 Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis. United States. doi:10.1145/2807591.2807663.
Sewell, Christopher, Messer, Bronson, Habib, Salman, Ahrens, James, Heitmann, Katrin, Finkel, Hal, Zagaris, George, Parete-Koon, Suzanne T., Fasel, Patricia K., Pope, Adrian, Frontiere, Nicholas, and Lo, Li-ta. Thu . "Large-scale compute-intensive analysis via a combined in-situ and co-scheduling workflow approach, In: SC '15 Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis". United States. doi:10.1145/2807591.2807663.
@article{osti_1567400,
title = {Large-scale compute-intensive analysis via a combined in-situ and co-scheduling workflow approach, In: SC '15 Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis},
author = {Sewell, Christopher and Messer, Bronson and Habib, Salman and Ahrens, James and Heitmann, Katrin and Finkel, Hal and Zagaris, George and Parete-Koon, Suzanne T. and Fasel, Patricia K. and Pope, Adrian and Frontiere, Nicholas and Lo, Li-ta},
abstractNote = {Large-scale simulations can produce hundreds of terabytes to petabytes of data, complicating and limiting the efficiency of workflows. Traditionally, outputs are stored on the file system and analyzed in post-processing. With the rapidly increasing size and complexity of simulations, this approach faces an uncertain future. Trending techniques consist of performing the analysis in-situ, utilizing the same resources as the simulation, and/or off-loading subsets of the data to a compute-intensive analysis system. We introduce an analysis framework developed for HACC, a cosmological N-body code, that uses both in-situ and co-scheduling approaches for handling petabyte-scale outputs. We compare different analysis set-ups ranging from purely off-line, to purely in-situ to in-situ/co-scheduling. The analysis routines are implemented using the PISTON/VTK-m framework, allowing a single implementation of an algorithm that simultaneously targets a variety of GPU, multi-core, and many-core architectures.},
doi = {10.1145/2807591.2807663},
journal = {PROCEEDINGS OF SC15: THE INTERNATIONAL CONFERENCE FOR HIGH PERFORMANCE COMPUTING, NETWORKING, STORAGE AND ANALYSIS},
number = ,
volume = ,
place = {United States},
year = {2015},
month = {1}
}

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