Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/53796
Title: Monte Carlo scalable algorithms for Computational Finance
Authors: Alexandrov, V. N.
Gonzalez Martel, Christian 
Strassburg, J.
UNESCO Clasification: 120302 Lenguajes algorítmicos
Keywords: Scalable algorithms
Computational finance
Monte Carlo
Issue Date: 2011
Publisher: 1877-0509
Journal: Procedia Computer Science 
Conference: 11th International Conference on Computational Science, ICCS 2011 
Abstract: With the latest developments in the area of advanced computer architectures, we are already seeing large scale machines at petascale level and we are faced with the exascale computing challenge. All these require scalability at system, algorithmic and mathematical model level. In particular, e_cient scalable algorithms are required to bridge the performance gap. In this paper, examples of various approaches of designing scalable algorithms for such advanced architectures will be given. We will briefly present our approach to Monte Carlo scalable algorithms for Linear Algebra and explain how these approaches are extended to the field of Computational Finance. Implementation examples will be presented using Linear Algebra Problems and problems from Computational Finance. Furthermore, the corresponding properties of these algorithms will be outlined and discussed.
URI: http://hdl.handle.net/10553/53796
ISSN: 1877-0509
DOI: 10.1016/j.procs.2011.04.185
Source: Proceedings Of The International Conference On Computational Science (Iccs) [ISSN 1877-0509], v. 4, p. 1708-1715
Appears in Collections:Actas de congresos
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