Mapping of option pricing algorithms onto heterogeneous many-core architectures

被引：0
作者：
Shuai Zhang
Zhao Wang
Ying Peng
Bertil Schmidt
Weiguo Liu
机构：
[1] Shandong University,School of Computer Science and Technology
[2] Shandong University,ZhongTai Securities Institute for Financial Studies
[3] Johannes Gutenberg University,undefined
来源：
The Journal of Supercomputing | 2017年 / 73卷
关键词：
Heterogeneous many-core architecture; European option pricing; American option pricing; GPU; Xeon Phi;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The rapid development of technologies and applications in recent years poses high demands and challenges for high-performance computing. Because of their competitive performance/price ratio, heterogeneous many-core architectures are widely used in high-performance computing areas. GPU and Xeon Phi are two popular general-purpose many-core accelerators. In this paper, we demonstrate how heterogeneous many-core architectures, powered by multi-core CPUs, CUDA-enabled GPUs and Xeon Phis can be used as an efficient computational platform to accelerate popular option pricing algorithms. In order to make full use of the compute power of this architecture, we have used a hybrid computing model which consists of two types of data parallelism: worker level and device level. The worker level data parallelism uses a distributed computing infrastructure for task distribution, while the device level data parallelism uses both the multi-core CPUs and many-core accelerators for fast option pricing calculation. Experiments show that our implementations achieve good performance and scalability on this architecture and also outperform other state-of-the-art GPU-based solutions for Monte Carlo European/American option pricing and BSDE European option pricing.
引用
收藏
页码：3715 / 3737
页数：22
相关论文
共 41 条
  • [1] Zenios SA(1999)High-performance computing in finance: the last 10 years and the next Parallel Comput 25 2149-2175
  • [2] Li JX(2000)Parallel computing of a quasi-Monte Carlo algorithm for valuing derivatives Parallel Comput 26 641-653
  • [3] Mullen GL(2004)Architecture independent parallel binomial tree option price valuations Parallel Comput 30 301-316
  • [4] Gerbessiotis AV(2007)Parallel computing in Asian option pricing Parallel Comput 33 92-108
  • [5] Sak H(1996)Parallel stereocorrelation on a reconfigurable multi-ring network J Supercomput 10 243-269
  • [6] Özekici S(2003)Parallel edge-region-based segmentation algorithm targeted at reconfigurable multiring network J Supercomput 25 43-62
  • [7] Bodurog İ(1973)Conjugate convex functions in optimal stochastic control J Math Anal Appl 44 384-404
  • [8] Arabnia HR(1973)The pricing of options and corporate liabilities J Polit Econ 81 637-654
  • [9] Bhandarkar SM(2010)Stochastic differential equations and application of the Kalman–Bucy filter in the modeling of RC circuit Appl Math Sci 4 1119-1127
  • [10] Wani MA(1979)Option pricing: a simplified approach J Financ Econ 7 229-263
12345