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Publication

A Codesign Framework for Online Data Analysis and Reduction...

Publication Type
Conference Paper
Book Title
2019 IEEE/ACM Workflows in Support of Large-Scale Science (WORKS)
Publication Date
Page Numbers
11 to 20
Conference Name
WORKS 2019 Workshop on Workflows in Support of Large-Scale Science, held in conjunction with SC19: The International Conference for High Performance Computing, Networking, Storage, and Analysis
Conference Location
Denver, Colorado, United States of America
Conference Sponsor
ACM, Sighpc, IEEE, TCHPC
Conference Date

In this paper we discuss our design of a toolset for automating performance studies of composed HPC applications that perform online data reduction and analysis. We describe Cheetah, a new framework for performing parametric studies on coupled applications. Cheetah facilitates understanding the impact of various factors such as process placement, synchronicity of algorithms, and storage vs. compute requirements for online analysis of large data. Ultimately, we aim to create a catalog of performance results that can help scientists understand tradeoffs when designing next-generation simulations that make use of online processing techniques. We illustrate the design choices of Cheetah by using a reaction-diffusion simulation (Gray-Scott) paired with an analysis application to demonstrate initial results of fine-grained process placement on Summit, a pre-exascale supercomputer at Oak Ridge National Laboratory.