research-article

High-Performance Quasi-Monte Carlo Financial Simulation: FPGA vs. GPP vs. GPU

Authors:

Khaled BenkridAuthors Info & Claims

ACM Transactions on Reconfigurable Technology and Systems (TRETS), Volume 3, Issue 4

Article No.: 26, Pages 1 - 22

https://doi.org/10.1145/1862648.1862656

Published: 01 November 2010 Publication History

Abstract

Quasi-Monte Carlo simulation is a special Monte Carlo simulation method that uses quasi-random or low-discrepancy numbers as random sample sets. In many applications, this method has proved advantageous compared to the traditional Monte Carlo simulation method, which uses pseudo-random numbers, thanks to its faster convergence and higher level of accuracy. This article presents the design and implementation of a massively parallelized Quasi-Monte Carlo simulation engine on an FPGA-based supercomputer, called Maxwell. It also compares this implementation with equivalent graphics processing units (GPUs) and general purpose processors (GPP)-based implementations. The detailed comparison between these three implementations (FPGA vs. GPP vs. GPU) is done in the context of financial derivatives pricing based on our Quasi-Monte Carlo simulation engine. Real hardware implementations on the Maxwell machine show that FPGAs outperform equivalent GPP-based software implementations by 2 orders of magnitude, with the speed-up figure scaling linearly with the number of processing nodes used (FPGAs/GPPs). The same implementations show that FPGAs achieve a ~ 3x speedup compared to equivalent GPU-based implementations. Power consumption measurements also show FPGAs to be 336x more energy efficient than CPUs, and 16x more energy efficient than GPUs.

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Cited By

Prouveur CHaefele MKenter TVoss NHuebl ASilvano CRobinson T(2023)FPGA Acceleration for HPC Supercapacitor SimulationsProceedings of the Platform for Advanced Scientific Computing Conference10.1145/3592979.3593419(1-11)Online publication date: 26-Jun-2023
https://dl.acm.org/doi/10.1145/3592979.3593419
Pinto PBispo JCardoso JBarbosa JGadioli DPalermo GMartinovic JGolasowski MSlaninova KCmar RSilvano C(2022)Pegasus: Performance Engineering for Software Applications Targeting HPC SystemsIEEE Transactions on Software Engineering10.1109/TSE.2020.300125748:3(732-754)Online publication date: 1-Mar-2022
https://doi.org/10.1109/TSE.2020.3001257
Asadova FKertesz GLovas RSzenasi S(2022)Fault detection in GPU-enabled Cloud Systems – An Overview2022 IEEE 20th Jubilee World Symposium on Applied Machine Intelligence and Informatics (SAMI)10.1109/SAMI54271.2022.9780804(000317-000322)Online publication date: 2-Mar-2022
https://doi.org/10.1109/SAMI54271.2022.9780804
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Index Terms

High-Performance Quasi-Monte Carlo Financial Simulation: FPGA vs. GPP vs. GPU
1. Hardware
  1. Emerging technologies
  2. Very large scale integration design

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Published In

cover image ACM Transactions on Reconfigurable Technology and Systems

ACM Transactions on Reconfigurable Technology and Systems Volume 3, Issue 4

November 2010

240 pages

ISSN:1936-7406

EISSN:1936-7414

DOI:10.1145/1862648

Issue’s Table of Contents

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 01 November 2010

Accepted: 01 September 2009

Revised: 01 July 2009

Received: 01 February 2009

Published in TRETS Volume 3, Issue 4

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Cited By

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https://dl.acm.org/doi/10.1145/3592979.3593419
Pinto PBispo JCardoso JBarbosa JGadioli DPalermo GMartinovic JGolasowski MSlaninova KCmar RSilvano C(2022)Pegasus: Performance Engineering for Software Applications Targeting HPC SystemsIEEE Transactions on Software Engineering10.1109/TSE.2020.300125748:3(732-754)Online publication date: 1-Mar-2022
https://doi.org/10.1109/TSE.2020.3001257
Asadova FKertesz GLovas RSzenasi S(2022)Fault detection in GPU-enabled Cloud Systems – An Overview2022 IEEE 20th Jubilee World Symposium on Applied Machine Intelligence and Informatics (SAMI)10.1109/SAMI54271.2022.9780804(000317-000322)Online publication date: 2-Mar-2022
https://doi.org/10.1109/SAMI54271.2022.9780804
Mahony AZeidan GHanzon BPopovici E(2022)A parallel and pipelined implementation of a pascal-simplex based multi-asset option pricer on FPGA using OpenCLMicroprocessors & Microsystems10.1016/j.micpro.2022.10450890:COnline publication date: 1-Apr-2022
https://dl.acm.org/doi/10.1016/j.micpro.2022.104508
Mahony AZeidan GHanzon BPopovici E(2020)A Parallel and Pipelined Implementation of a Pascal-Simplex Based Two Asset Option Pricer on FPGA using OpenCL2020 IEEE Nordic Circuits and Systems Conference (NorCAS)10.1109/NorCAS51424.2020.9264992(1-6)Online publication date: 27-Oct-2020
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Mannatunga KAli SCrespo MCicuttin ASamarawikrama J(2020)High Performance 128-Channel Acquisition System for Electrophysiological SignalsIEEE Access10.1109/ACCESS.2020.30070828(122366-122383)Online publication date: 2020
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Peri A(2020)A Hardware Approach to Value Function IterationJournal of Economic Dynamics and Control10.1016/j.jedc.2020.103894(103894)Online publication date: Mar-2020
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Chamberlain R(2020)Architecturally truly diverse systems: A reviewFuture Generation Computer Systems10.1016/j.future.2020.03.061Online publication date: Apr-2020
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Bhagirath Mittal NKumar S(2019)Machine Learning Computation on Multiple GPU's using CUDA and Message Passing Interface2019 2nd International Conference on Power Energy, Environment and Intelligent Control (PEEIC)10.1109/PEEIC47157.2019.8976714(18-22)Online publication date: Oct-2019
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Sedighi AJacobson D(2019)Computational Challenges and Opportunities in Financial ServicesSmart Computing and Communication10.1007/978-3-030-34139-8_31(310-319)Online publication date: 11-Oct-2019
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