PARSEC* 3.0 中的多线程代码优化: BlackScholes

The Black-Scholes benchmark is a one of the 13 benchmarks in the PARSEC. This benchmark does option pricing with Black-Scholes Partial Differential Equation (PDE). The Black-Scholes equation is a differential equation that describes how, under a certain set of assumptions, the value of an option changes as the price of the underlying asset changes. Based on this formula, one can compute the...
Authored by Artem G. (Intel) Last updated on 07/04/2019 - 21:42

案例研究: 使用分布式优化框架在 Monte Carlo 欧式期权方面实现高级性能

1. 简介

Monte Carlo 使用统计计算方法解决复杂的科学计算问题。 它创新地使用随机数字模拟一个问题输入结果的不确定性,并通过处理重复的参数抽样获得一个确定的结果和解决一些以其他方式无法解决的问题。 该方法最早起源于上世纪 40 年代末,由参与“曼哈顿”计划的核物理学家们率先提出。 并采用摩纳哥最大的赌城 Monte Carlo 来命名。

Authored by Last updated on 07/06/2019 - 16:40

借助 SIMD 数据布局模板优化数据布局

Financial service customers need to improve financial algorithmic performance for models such as Monte Carlo, Black-Scholes, and others. SIMD programming can speed up these workloads. In this paper, we perform data layout optimizations using two approaches on a Black-Scholes workload for European options valuation from the open source Quantlib library.
Authored by Nimisha R. (Intel) Last updated on 12/12/2018 - 18:00