Abstract
Financial applications are one of many fields where a multivariate Gaussian random number generator plays a key role in performing computationally extensive simulations. Recent technological advances and today’s requirements have led to the migration of the traditional software based multivariate Gaussian random number generator to a hardware based model. Field Programmable Gate Arrays (FPGA) are normally used as a target device due to their fine grain parallelism and reconfigurability. As well as the ability to achieve designs with high throughput it is also desirable to produce designs with the flexibility to control the resource usage in order to meet given resource constraints. This paper proposes an algorithm for a multivariate Gaussian random number generator implementation in an FPGA given a set of resources to be utilized. Experiments demonstrate the proposed algorithm’s capability of producing a design that meets any given resource constraints.
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Saiprasert, C., Bouganis, CS., Constantinides, G.A. (2008). Multivariate Gaussian Random Number Generator Targeting Specific Resource Utilization in an FPGA. In: Woods, R., Compton, K., Bouganis, C., Diniz, P.C. (eds) Reconfigurable Computing: Architectures, Tools and Applications. ARC 2008. Lecture Notes in Computer Science, vol 4943. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78610-8_23
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DOI: https://doi.org/10.1007/978-3-540-78610-8_23
Publisher Name: Springer, Berlin, Heidelberg
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