University of Illinois Urbana-Champaign

Optimization and Parallelization of a Time Series Classification Algorithm

Sinkovits, Robert S.

Content Files
XSEDE-20191-Optimizationandparallelizationofatimeseriesclassificationalgorithm_SinkovitsHuertav2.pdf

Permalink

https://hdl.handle.net/2142/104713

Description

Title
Optimization and Parallelization of a Time Series Classification Algorithm
Author(s)
Sinkovits, Robert S.
Contributor(s)
Huerta, Ramon
Issue Date
2019-08-20
Keyword(s)
  • XSEDE
  • Technical Report Series
  • optimization
  • parallelization
  • MKL
  • time-space tradeoff
  • time series algorithm
  • ECSS
  • Extended Collaborative Support Services
  • Ramon Huerta
Date of Ingest
2019-08-20T17:04:14Z
Abstract
This technical report describes the steps taken to optimize and parallelize a time series classification algorithm as part of an Extended Collaborative Support Services (ECSS) project with XSEDE researcher Ramon Huerta at the University of California, San Diego. Switching from the GNU compiler to the Intel compiler and enabling Advanced Vector Extensions (AVX) resulted in a 2x speedup, while linking to the Intel Math Kernel Library (MKL) instead of the default LAPACK library further improved performance and provided an easy path to thread-level parallel execution. These changes resulted in a combined 46x speedup relative to a single core when running on all 16 cores of a dual-socket Intel Sandy Bridge node. Parallelization of several loops using OpenMP directives and the removal of an unnecessary duplicate call to a computationally demanding routine brought the total speedup to 86x. Optimization of linear algebra operations using time-space tradeoffs ultimately resulted in a total speedup of 168x relative to the original version and build of the code.
Publisher
Extreme Science and Engineering Discovery Environment (XSEDE)
Series/Report Name or Number
XSEDE-2019.1
Type of Resource
text
Genre of Resource
Technical Report
Language
eng
Permalink
http://hdl.handle.net/2142/104713
DOI
https://doi.org/10.21900/XSEDE-2019.1
Sponsor(s)/Grant Number(s)
National Science Foundation OCI-1053575

Owning Collections

XSEDE Technical Report Series PRIMARY