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Title: Analytical Performance Modeling and Validation of Intel’s Xeon Phi Architecture

Abstract

Modeling the performance of scientific applications on emerging hardware plays a central role in achieving extreme-scale computing goals. Analytical models that capture the interaction between applications and hardware characteristics are attractive because even a reasonably accurate model can be useful for performance tuning before the hardware is made available. In this paper, we develop a hardware model for Intel’s second-generation Xeon Phi architecture code-named Knights Landing (KNL) for the SKOPE framework. We validate the KNL hardware model by projecting the performance of mini-benchmarks and application kernels. The results show that our KNL model can project the performance with prediction errors of 10% to 20%. The hardware model also provides informative recommendations for code transformations and tuning.

Authors:
; ; ; ;
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
OSTI Identifier:
1351827
DOE Contract Number:
AC02-06CH11357
Resource Type:
Conference
Resource Relation:
Conference: ACM International Conference on Computing Frontiers 2017, Siena (Italy), 15-17 May 2017
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; KNL; analytical modeling; benchmark; performance; projection

Citation Formats

Chunduri, Sudheer, Balaprakash, Prasanna, Morozov, Vitali, Vishwanath, Venkatram, and Kumaran, Kalyan. Analytical Performance Modeling and Validation of Intel’s Xeon Phi Architecture. United States: N. p., 2017. Web. doi:10.1145/3075564.3075593.
Chunduri, Sudheer, Balaprakash, Prasanna, Morozov, Vitali, Vishwanath, Venkatram, & Kumaran, Kalyan. Analytical Performance Modeling and Validation of Intel’s Xeon Phi Architecture. United States. doi:10.1145/3075564.3075593.
Chunduri, Sudheer, Balaprakash, Prasanna, Morozov, Vitali, Vishwanath, Venkatram, and Kumaran, Kalyan. Sun . "Analytical Performance Modeling and Validation of Intel’s Xeon Phi Architecture". United States. doi:10.1145/3075564.3075593. https://www.osti.gov/servlets/purl/1351827.
@article{osti_1351827,
title = {Analytical Performance Modeling and Validation of Intel’s Xeon Phi Architecture},
author = {Chunduri, Sudheer and Balaprakash, Prasanna and Morozov, Vitali and Vishwanath, Venkatram and Kumaran, Kalyan},
abstractNote = {Modeling the performance of scientific applications on emerging hardware plays a central role in achieving extreme-scale computing goals. Analytical models that capture the interaction between applications and hardware characteristics are attractive because even a reasonably accurate model can be useful for performance tuning before the hardware is made available. In this paper, we develop a hardware model for Intel’s second-generation Xeon Phi architecture code-named Knights Landing (KNL) for the SKOPE framework. We validate the KNL hardware model by projecting the performance of mini-benchmarks and application kernels. The results show that our KNL model can project the performance with prediction errors of 10% to 20%. The hardware model also provides informative recommendations for code transformations and tuning.},
doi = {10.1145/3075564.3075593},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sun Jan 01 00:00:00 EST 2017},
month = {Sun Jan 01 00:00:00 EST 2017}
}

Conference:
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