Performance of a Second Order Electrostatic Particle-in-Cell Algorithm on Modern Many-Core Architectures

Research output: Contribution to journalArticlepeer-review

Standard

Performance of a Second Order Electrostatic Particle-in-Cell Algorithm on Modern Many-Core Architectures. / Brown, Dominic A.S.; Wright, Steven A.; Jarvis, Stephen A.

In: Electronic Notes in Theoretical Computer Science, Vol. 340, 29.10.2018, p. 67-84.

Research output: Contribution to journalArticlepeer-review

Harvard

APA

Vancouver

Author

Bibtex

@article{328b2710360e479db9d679b0935c8f23,
title = "Performance of a Second Order Electrostatic Particle-in-Cell Algorithm on Modern Many-Core Architectures",
abstract = "In this paper we present the outline of a novel electrostatic, second order Particle-in-Cell (PIC) algorithm, that makes use of {\textquoteleft}ghost particles{\textquoteright} located around true particle positions in order to represent a charge distribution. We implement our algorithm within EMPIRE-PIC, a PIC code developed at Sandia National Laboratories. We test the performance of our algorithm on a variety of many-core architectures including NVIDIA GPUs, conventional CPUs, and Intel's Knights Landing. Our preliminary results show the viability of second order methods for PIC applications on these architectures when compared to previous generations of many-core hardware. Specifically, we see an order of magnitude improvement in performance for second order methods between the Tesla K20 and Tesla P100 GPU devices, despite only a 4× improvement in the theoretical peak performance between the devices. Although these initial results show a large increase in runtime over first order methods, we hope to be able to show improved scaling behaviour and increased simulation accuracy in the future.",
keywords = "Broadwell, GPU, K20, KNL, Many-Core, P100, Particle-in-Cell, PIC, Second Order Algorithms",
author = "Brown, {Dominic A.S.} and Wright, {Steven A.} and Jarvis, {Stephen A.}",
note = "Funding Information: This work was supported by the UK Atomic Weapons Establishment (AWE) under grant CDK0724 (AWE Technical Outreach Programme). Professor Stephen Jarvis is an AWE William Penney Fellow. Publisher Copyright: {\textcopyright} 2018",
year = "2018",
month = oct,
day = "29",
doi = "10.1016/j.entcs.2018.09.006",
language = "English",
volume = "340",
pages = "67--84",
journal = "Electronic Notes in Theoretical Computer Science",
issn = "1571-0661",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Performance of a Second Order Electrostatic Particle-in-Cell Algorithm on Modern Many-Core Architectures

AU - Brown, Dominic A.S.

AU - Wright, Steven A.

AU - Jarvis, Stephen A.

N1 - Funding Information: This work was supported by the UK Atomic Weapons Establishment (AWE) under grant CDK0724 (AWE Technical Outreach Programme). Professor Stephen Jarvis is an AWE William Penney Fellow. Publisher Copyright: © 2018

PY - 2018/10/29

Y1 - 2018/10/29

N2 - In this paper we present the outline of a novel electrostatic, second order Particle-in-Cell (PIC) algorithm, that makes use of ‘ghost particles’ located around true particle positions in order to represent a charge distribution. We implement our algorithm within EMPIRE-PIC, a PIC code developed at Sandia National Laboratories. We test the performance of our algorithm on a variety of many-core architectures including NVIDIA GPUs, conventional CPUs, and Intel's Knights Landing. Our preliminary results show the viability of second order methods for PIC applications on these architectures when compared to previous generations of many-core hardware. Specifically, we see an order of magnitude improvement in performance for second order methods between the Tesla K20 and Tesla P100 GPU devices, despite only a 4× improvement in the theoretical peak performance between the devices. Although these initial results show a large increase in runtime over first order methods, we hope to be able to show improved scaling behaviour and increased simulation accuracy in the future.

AB - In this paper we present the outline of a novel electrostatic, second order Particle-in-Cell (PIC) algorithm, that makes use of ‘ghost particles’ located around true particle positions in order to represent a charge distribution. We implement our algorithm within EMPIRE-PIC, a PIC code developed at Sandia National Laboratories. We test the performance of our algorithm on a variety of many-core architectures including NVIDIA GPUs, conventional CPUs, and Intel's Knights Landing. Our preliminary results show the viability of second order methods for PIC applications on these architectures when compared to previous generations of many-core hardware. Specifically, we see an order of magnitude improvement in performance for second order methods between the Tesla K20 and Tesla P100 GPU devices, despite only a 4× improvement in the theoretical peak performance between the devices. Although these initial results show a large increase in runtime over first order methods, we hope to be able to show improved scaling behaviour and increased simulation accuracy in the future.

KW - Broadwell

KW - GPU

KW - K20

KW - KNL

KW - Many-Core

KW - P100

KW - Particle-in-Cell

KW - PIC

KW - Second Order Algorithms

UR - http://www.scopus.com/inward/record.url?scp=85055719369&partnerID=8YFLogxK

U2 - 10.1016/j.entcs.2018.09.006

DO - 10.1016/j.entcs.2018.09.006

M3 - Article

AN - SCOPUS:85055719369

VL - 340

SP - 67

EP - 84

JO - Electronic Notes in Theoretical Computer Science

JF - Electronic Notes in Theoretical Computer Science

SN - 1571-0661

ER -