Run-time reconfigurable acceleration for genetic programming fitness evaluation in trading strategies

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Title: Run-time reconfigurable acceleration for genetic programming fitness evaluation in trading strategies
Authors: Funie, AI
Grigoras, P
Burovskiy, P
Luk, W
Salmon, M
Item Type: Journal Article
Abstract: Genetic programming can be used to identify complex patterns in financial markets which may lead to more advanced trading strategies. However, the computationally intensive nature of genetic programming makes it difficult to apply to real world problems, particularly in real-time constrained scenarios. In this work we propose the use of Field Programmable Gate Array technology to accelerate the fitness evaluation step, one of the most computationally demanding operations in genetic programming. We propose to develop a fully-pipelined, mixed precision design using run-time reconfiguration to accelerate fitness evaluation. We show that run-time reconfiguration can reduce resource consumption by a factor of 2 compared to previous solutions on certain configurations. The proposed design is up to 22 times faster than an optimised, multithreaded software implementation while achieving comparable financial returns.
Issue Date: 8-May-2017
Date of Acceptance: 2-Apr-2017
URI: http://hdl.handle.net/10044/1/52831
DOI: https://dx.doi.org/10.1007/s11265-017-1244-8
ISSN: 1939-8018
Publisher: Springer
Start Page: 39
End Page: 52
Journal / Book Title: Journal of Signal Processing Systems
Volume: 90
Issue: 1
Copyright Statement: © The Author(s) 2017. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Sponsor/Funder: Engineering & Physical Science Research Council (EPSRC)
Engineering & Physical Science Research Council (E
Commission of the European Communities
Engineering & Physical Science Research Council (E
Funder's Grant Number: EP/I012036/1
PO 1553380
671653
516075101 (EP/N031768/1)
Keywords: Science & Technology
Technology
Computer Science, Information Systems
Engineering, Electrical & Electronic
Computer Science
Engineering
Fitness evaluation
Genetic programming
High-frequency trading
Run-time reconfiguration
RULES
0906 Electrical And Electronic Engineering
Networking & Telecommunications
Computer Hardware & Architecture
Publication Status: Published
Open Access location: https://link.springer.com/article/10.1007/s11265-017-1244-8
Appears in Collections:Faculty of Engineering
Computing



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