Reconfigurable acceleration of fitness evaluation in trading strategies

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Funie:2015:ieeeASAP,

• author = "Andreea Ingrid Funie and Paul Grigoras and Pavel Burovskiy and Wayne Luk and Mark Salmon",
• booktitle = "26th IEEE International Conference on Application-specific Systems, Architectures and Processors (ASAP)",
• title = "Reconfigurable acceleration of fitness evaluation in trading strategies",
• year = "2015",
• pages = "210--217",
• month = "27-29 " # jul,
• address = "Toronto, Canada",
• keywords = "genetic algorithms, genetic programming, FPGA, Field programmable gate arrays, Random access memory, Clocks, Acceleration, Sociology, Statistics",
• ISSN = "1063-6862",
• URL = "https://www.doc.ic.ac.uk/~wl/papers/15/asap15if.pdf",
• DOI = "doi:10.1109/ASAP.2015.7245736",
• size = "8 pages",
• abstract = "Over the past years, examining financial markets has become a crucial part of both the trading and regulatory processes. Recently, genetic programs have been used to identify patterns in financial markets which may lead to more advanced trading strategies. We investigate the use of Field Programmable Gate Arrays to accelerate the evaluation of the fitness function which is an important kernel in genetic programming. Our pipelined design makes use of the massive amounts of parallelism available on chip to evaluate the fitness of multiple genetic programs simultaneously. An evaluation of our designs on both synthetic and historical market data shows that our implementation evaluates fitness function up to 21.56 times faster than a multi-threaded C++11 implementation running on two six-core Intel Xeon E5-2640 processors using OpenMP.",
• notes = "Also known as \cite{7245736}",

}

Genetic Programming entries for Andreea Ingrid Cross Paul Grigoras Pavel Burovskiy Wayne Luk Mark Salmon

Citations