A hardware generator for multi-point distributed random variables

Martini, F; Piccardi, M; Liberatiy, NB; Plateny, E

A hardware generator for multi-point distributed random variables

Martini, F Piccardi, M

Liberatiy, NB Plateny, E

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Publication Type:: Conference Proceeding
Citation:: Proceedings - IEEE International Symposium on Circuits and Systems, 2005, pp. 1702 - 1705
Issue Date:: 2005-12-01

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Field	Value	Language
dc.contributor.author	Martini, F	en_US
dc.contributor.author	Piccardi, M https://orcid.org/0000-0001-9250-6604	en_US
dc.contributor.author	Liberatiy, NB	en_US
dc.contributor.author	Plateny, E https://orcid.org/0000-0003-4595-3123	en_US
dc.date.issued	2005-12-01	en_US
dc.identifier.citation	Proceedings - IEEE International Symposium on Circuits and Systems, 2005, pp. 1702 - 1705	en_US
dc.identifier.issn	0271-4310	en_US
dc.identifier.uri	http://hdl.handle.net/10453/2850
dc.description.abstract	In Monte Carlo simulation of weak approximation of stochastic differential equations, multi-point distributed random variables play an important role. However, they need highly efficient implementations to meet the "real-time" requirements of applications such as the pricing of complex derivative securities. In this paper a fast and fexible dedicated hardware generator of multi-point distributed random variables on a Field Programmable Gate Array (FPGA) is presented. A comparative performance analysis demonstrates that the hardware solution is bottleneck-free, retains the fexibility of a traditional software implementation and significantly increases the computational fficiency of the overall simulation. © 2005 IEEE.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP0343913
dc.relation.ispartof	Proceedings - IEEE International Symposium on Circuits and Systems	en_US
dc.relation.isbasedon	10.1109/ISCAS.2005.1464934	en_US
dc.title	A hardware generator for multi-point distributed random variables	en_US
dc.type	Conference Proceeding
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
dc.location.activity	Kobe, Japan	en_US
dc.location.activity	Kobe, JAPAN
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - QFRC - Quantitative Finance Research Centre
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US

Abstract:

In Monte Carlo simulation of weak approximation of stochastic differential equations, multi-point distributed random variables play an important role. However, they need highly efficient implementations to meet the "real-time" requirements of applications such as the pricing of complex derivative securities. In this paper a fast and fexible dedicated hardware generator of multi-point distributed random variables on a Field Programmable Gate Array (FPGA) is presented. A comparative performance analysis demonstrates that the hardware solution is bottleneck-free, retains the fexibility of a traditional software implementation and significantly increases the computational fficiency of the overall simulation. © 2005 IEEE.

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http://hdl.handle.net/10453/2850