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Optimization of Binomial Option Pricing on Intel MIC Heterogeneous System

机译:Intel MIC异构系统上二项式期权定价的优化

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In these years, computerization has been more and more important in the financial area. The computational intensity and realtime constraints of those financial models require high-throughput parallel architectures. In this paper, optimization of widely-used binomial option pricing model has been implemented on the worlds largest supercomputer, Tianhe-2. In our work, we employ several optimizing techniques to efficiently utilize the architecture of Intel MIC heterogeneous system to improve the performance. The experimental results show that, compared with the serial implementation, the optimized binomial option pricing achieves 33X speedup on one Intel Xeon CPU and 61X speedup on one Intel Xeon Phi coprocessor. Further experiments on Intel MIC heterogeneous system indicate that our implementation attains a speedup factor of 254 on one Tianhe-2 computing node.
机译:近年来,计算机化在金融领域变得越来越重要。这些财务模型的计算强度和实时约束要求高吞吐量的并行体系结构。本文在世界上最大的超级计算机天河2号上实现了广泛使用的二项式期权定价模型的优化。在我们的工作中,我们采用了几种优化技术来有效利用英特尔MIC异构系统的体系结构来提高性能。实验结果表明,与串行实现相比,优化的二项式期权定价在一个Intel Xeon CPU上实现了33倍的加速,在一个Intel Xeon Phi协处理器上实现了61倍的加速。在Intel MIC异构系统上的进一步实验表明,我们的实现在一个Tianhe-2计算节点上达到了254的加速因子。

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