First Advisor

Karen Karavanic

Date of Award

3-1-2019

Document Type

Thesis

Degree Name

Bachelor of Science (B.S.) in Computer Science and University Honors

Department

Computer Science

Language

English

Subjects

High performance computing, Time-series analysis, Databases, Trace analysis

DOI

10.15760/honors.780

Abstract

In this work, I demonstrate that a time series database can be utilized to store Open Trace Format 2 (OTF2) file metadata for common trace events efficiently and scalably. This paper examines the efficacy of storing event trace data in a time series database, and investigates associated performance overhead compared to the state of the art method using OTF2 trace files. The sample traces used in this project are generated from a parallel hydrodynamic modeling code, Lulesh, developed at Lawrence Livermore National Laboratory. In my approach, I first cache common event trace metadata in InfluxDB, a contemporary time series database. Next, I compare the runtime performance of various metrics by executing InfluxQL queries on InfluxDB, and using corresponding one-pass algorithms on the OTF2 trace files. My results reflect an exponential performance improvement benefitting the InfluxDB technique.

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In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/ This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).

Persistent Identifier

https://archives.pdx.edu/ds/psu/29059

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