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Title: Performance Issues of SYRK Implementations in Shared Memory Environments for Edge Cases

Abstract

The symmetric rank-k update (SYRK) is a level-3 BLAS routine commonly used by many Data Mining/Machine Learning(DM/ML) algorithms such as regression, dimensionality reduction algorithms like PCA, matrix factorization and k-mean clustering. This paper presents a comprehensive analysis of the SYRK routine under popular dense linear algebra libraries such as OpenBLAS, Intel MKL, and BLIS particularly focusing on edge cases of dense matrices (thin or fat shapes) that are common in DM/ML applications. Our work identifies some performance issues of the SYRK routine in multi-threaded shared memory environments for edge cases and discuss matrix dependent modifications for performance improvement.

Authors:
 [1];  [1];  [1];  [1];  [1]; ORCiD logo [2]
  1. Tennessee Technological University (TTU)
  2. ORNL
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:
1557469
DOE Contract Number:  
AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: 2018 21st International Conference of Computer and Information Technology (ICCIT) - Dhaka, , Bangladesh - 12/21/2018 10:00:00 AM-12/23/2018 5:00:00 AM
Country of Publication:
United States
Language:
English

Citation Formats

Hossain, Md Mosharaf, Hines, Thomas M., Ghafoor, Sheikh, Marshall, Ryan, Amanzholov, Muzakhir S., and Kannan, Ramakrishnan. Performance Issues of SYRK Implementations in Shared Memory Environments for Edge Cases. United States: N. p., 2018. Web. doi:10.1109/ICCITECHN.2018.8631936.
Hossain, Md Mosharaf, Hines, Thomas M., Ghafoor, Sheikh, Marshall, Ryan, Amanzholov, Muzakhir S., & Kannan, Ramakrishnan. Performance Issues of SYRK Implementations in Shared Memory Environments for Edge Cases. United States. https://doi.org/10.1109/ICCITECHN.2018.8631936
Hossain, Md Mosharaf, Hines, Thomas M., Ghafoor, Sheikh, Marshall, Ryan, Amanzholov, Muzakhir S., and Kannan, Ramakrishnan. 2018. "Performance Issues of SYRK Implementations in Shared Memory Environments for Edge Cases". United States. https://doi.org/10.1109/ICCITECHN.2018.8631936. https://www.osti.gov/servlets/purl/1557469.
@article{osti_1557469,
title = {Performance Issues of SYRK Implementations in Shared Memory Environments for Edge Cases},
author = {Hossain, Md Mosharaf and Hines, Thomas M. and Ghafoor, Sheikh and Marshall, Ryan and Amanzholov, Muzakhir S. and Kannan, Ramakrishnan},
abstractNote = {The symmetric rank-k update (SYRK) is a level-3 BLAS routine commonly used by many Data Mining/Machine Learning(DM/ML) algorithms such as regression, dimensionality reduction algorithms like PCA, matrix factorization and k-mean clustering. This paper presents a comprehensive analysis of the SYRK routine under popular dense linear algebra libraries such as OpenBLAS, Intel MKL, and BLIS particularly focusing on edge cases of dense matrices (thin or fat shapes) that are common in DM/ML applications. Our work identifies some performance issues of the SYRK routine in multi-threaded shared memory environments for edge cases and discuss matrix dependent modifications for performance improvement.},
doi = {10.1109/ICCITECHN.2018.8631936},
url = {https://www.osti.gov/biblio/1557469}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Sat Dec 01 00:00:00 EST 2018},
month = {Sat Dec 01 00:00:00 EST 2018}
}

Conference:
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