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Cache-Optimal Algorithms for Option Pricing

机译:期权定价的缓存优化算法

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摘要

Today computers have several levels of memory hierarchy. To obtain good performance on these processors it is necessary to design algorithms that minimize I/O traffic to slower memories in the hierarchy. In this article, we study the computation of option pricing using the binomial and trinomial models on processors with a multilevel memory hierarchy. We derive lower bounds on memory traffic between different levels of the hierarchy for these two models. We also develop algorithms for the binomial and trinomial models that have near-optimal memory traffic between levels. We have implemented these algorithms on an UltraSparc IIIi processor with a 4-level of memory hierarchy and demonstrated that our algorithms outperform algorithms without cache blocking by a factor of up to 5 and operate at 70% of peak performance.
机译:如今,计算机具有几种级别的内存层次结构。为了在这些处理器上获得良好的性能,必须设计最小化I / O流量以降低层次结构中的内存的算法。在本文中,我们研究了在具有多级内存层次结构的处理器上使用二项式和三项式模型进行的期权定价计算。对于这两个模型,我们得出层次结构的不同级别之间的内存流量下限。我们还开发了用于二项式和三项式模型的算法,这些算法在级别之间具有接近最佳的内存流量。我们已经在具有4级内存层次结构的UltraSparc IIIi处理器上实现了这些算法,并证明了我们的算法在没有缓存阻塞的情况下的性能要比算法高出5倍,并且可以在70%的峰值性能下运行。

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