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FPGA-Based Reconfigurable Computing for Pricing Multi-asset Barrier Options

机译:基于FPGA的可重新配置计算,用于定价多资产屏障选项

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Multi-asset barrier contracts are path-dependent exotic options consisting of two or more underlying assets. As the dimensions of an option increase, so does the mathematical complexity of a closed form solution. Monte Carlo (MC) methods offer an attractive solution under such conditions. MC methods have an O(n-1/2) convergence rate irrespective of the dimension of the integral. However, such methods using conventional computing with CPUs are not scalable enough to enable banks to realize the potential that these exotic options promise. This paper presents an FPGA-based accelerated system architecture to price multi-asset barrier contracts. The architecture consists of a parallel set of Monte Carlo cores, each capable of simulating multiple Monte Carlo paths. Each MC core is designed to be customizable so that the core for the model (i.e., "model" core) can be easily replaced. In our current design, a Heston core based on the full truncation Euler discretization method is used as the model core. Similarly, we can use different payoff calculator kernels to compute various payoffs such as vanilla portfolios, barriers, look-backs, etc. The design leverages an early termination condition of "out" barrier options to efficiently schedule MC paths across multiple cores in a single FPGA and across multiple FPGAs. The target platform for our design is Novo-G, a reconfigurable supercomputer housed at the NSF Center for High-Performance Reconfigurable Computing (CHREC), University of Florida. Our design is validated for the single-asset configuration by comparing our output to option prices calculated analytically and achieves an average speedup of ranging from 123 to 350 on one FPGA as we vary the number of underlying assets from 32 down to 4. For a configuration with 16 underlying assets, the speedup achieved is 7134 when scaled to 48 FPGAs as compared to a single-threaded version of an SSE2-optimized C program running on a single Intel Sandy- Bridge E5-2687 core at 3.1 GHz with hyper-threading turned on. Finally, the techniques described in this paper can be applied to other exotic multi-asset option classes, such as look backs, rainbows, and Asian-style options.
机译:多资产屏障合同是由两种或多种潜在资产组成的路径依赖性异国情调。随着选择的尺寸增加,闭合形式解决方案的数学复杂性也是如此。 Monte Carlo(MC)方法在此类条件下提供有吸引力的解决方案。 MC方法具有o(n-1/2)的收敛速度,而不管积分的尺寸如何。然而,使用与CPU的传统计算的这种方法不可缩放,以使银行能够实现这些异国情调选项承诺的可能性。本文介绍了基于FPGA的加速系统架构,以价格多资产屏障合同。该架构由一组平行的蒙特卡罗核心组成,每个都能够模拟多个蒙特卡罗路径。每个MC核心都设计为可定制,以便可以轻松更换模型的核心(即“模型”核心)。在我们当前的设计中,基于完整截断欧拉离散化方法的Heston核心用作模型核心。同样,我们可以使用不同的收益计算器内核来计算各种收益,例如vanilla组合,障碍,回顾等。该设计利用了“Out”屏障选项的早期终止条件,以便在单个核心上有效地安排MC路径FPGA和跨多个FPGA。我们设计的目标平台是Novo-G,这是一个可重构的超级计算机,位于佛罗里达大学的NSF高性能可重新配置计算(Chrec)的NSF中心。我们的设计通过将我们的输出与分析计算的期权价格进行比较来验证单资产配置,并在一个FPGA上实现的平均加速度为123到350,因为我们改变32到4的底层资产数量。对于配置对于16个潜在资产,与在3.1 GHz上运行的SSE 2优化的C程序的单线程版本的单线程版本的SSE 2优化的C程序相比,在3.1GHz转动的SSE 2优化的C程序相比,实现了16134的Speedup在。最后,本文描述的技术可以应用于其他异国情调的多资产选项类,例如环形,彩虹和亚洲风格选项。

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