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Title: Fusion PIC code performance analysis on the Cori KNL system

Abstract

We study the attainable performance of Particle-In-Cell codes on the Cori KNL system by analyzing a miniature particle push application based on the fusion PIC code XGC1. We start from the most basic building blocks of a PIC code and build up the complexity to identify the kernels that cost the most in performance and focus optimization efforts there. Particle push kernels operate at high AI and are not likely to be memory bandwidth or even cache bandwidth bound on KNL. Therefore, we see only minor benefits from the high bandwidth memory available on KNL, and achieving good vectorization is shown to be the most beneficial optimization path with theoretical yield of up to 8x speedup on KNL. In practice we are able to obtain up to a 4x gain from vectorization due to limitations set by the data layout and memory latency.

Authors:
 [1];  [1];  [1];  [2]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)
  2. INTEL Corp. (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
OSTI Identifier:
1412519
DOE Contract Number:  
AC02-05CH11231
Resource Type:
Conference
Resource Relation:
Conference: Cray User Group Conference 2017, Redmond, WA (United States), 9-11 May 2017
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Koskela, Tuomas S., Deslippe, Jack, Friesen, Brian, and Raman, Karthic. Fusion PIC code performance analysis on the Cori KNL system. United States: N. p., 2017. Web.
Koskela, Tuomas S., Deslippe, Jack, Friesen, Brian, & Raman, Karthic. Fusion PIC code performance analysis on the Cori KNL system. United States.
Koskela, Tuomas S., Deslippe, Jack, Friesen, Brian, and Raman, Karthic. Thu . "Fusion PIC code performance analysis on the Cori KNL system". United States. doi:. https://www.osti.gov/servlets/purl/1412519.
@article{osti_1412519,
title = {Fusion PIC code performance analysis on the Cori KNL system},
author = {Koskela, Tuomas S. and Deslippe, Jack and Friesen, Brian and Raman, Karthic},
abstractNote = {We study the attainable performance of Particle-In-Cell codes on the Cori KNL system by analyzing a miniature particle push application based on the fusion PIC code XGC1. We start from the most basic building blocks of a PIC code and build up the complexity to identify the kernels that cost the most in performance and focus optimization efforts there. Particle push kernels operate at high AI and are not likely to be memory bandwidth or even cache bandwidth bound on KNL. Therefore, we see only minor benefits from the high bandwidth memory available on KNL, and achieving good vectorization is shown to be the most beneficial optimization path with theoretical yield of up to 8x speedup on KNL. In practice we are able to obtain up to a 4x gain from vectorization due to limitations set by the data layout and memory latency.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu May 25 00:00:00 EDT 2017},
month = {Thu May 25 00:00:00 EDT 2017}
}

Conference:
Other availability
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