Accelerating In-Transit Co-Processing for Scientific Simulations Using Region-Based Data-Driven Analysis

Increasing processing capabilities and input/output constraints of supercomputers have increased the use of co-processing approaches, i.e., visualizing and analyzing data sets of simulations on the fly. We present a method that evaluates the importance of different regions of simulation data and a d...

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Bibliographic Details
Published in:Algorithms Vol. 14; no. 5; p. 154
Main Authors: Walldén, Marcus, Okita, Masao, Ino, Fumihiko, Drikakis, Dimitris, Kokkinakis, Ioannis
Format: Journal Article
Language:English
Published: Basel MDPI AG 01.05.2021
Subjects:
co-processing
Data analysis
Data compression
Datasets
Fluid mechanics
in-transit
Methods
parallel computing
Performance evaluation
Richtmeyer-Meshkov instability
Simulation
Supercomputers
Visualization
ISSN:1999-4893, 1999-4893
Online Access:Get full text
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Summary:Increasing processing capabilities and input/output constraints of supercomputers have increased the use of co-processing approaches, i.e., visualizing and analyzing data sets of simulations on the fly. We present a method that evaluates the importance of different regions of simulation data and a data-driven approach that uses the proposed method to accelerate in-transit co-processing of large-scale simulations. We use the importance metrics to simultaneously employ multiple compression methods on different data regions to accelerate the in-transit co-processing. Our approach strives to adaptively compress data on the fly and uses load balancing to counteract memory imbalances. We demonstrate the method’s efficiency through a fluid mechanics application, a Richtmyer–Meshkov instability simulation, showing how to accelerate the in-transit co-processing of simulations. The results show that the proposed method expeditiously can identify regions of interest, even when using multiple metrics. Our approach achieved a speedup of 1.29× in a lossless scenario. The data decompression time was sped up by 2× compared to using a single compression method uniformly.
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content type line 14
ISSN:1999-4893
1999-4893
DOI:10.3390/a14050154