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用于亚洲期权定价的 Monte Carlo 模拟

This is an exercise in performance optimization on heterogeneous Intel architecture systems based on multi-core processors and manycore (MIC) coprocessors.
Authored by Mike P. (Intel) Last updated on 02/23/2017 - 22:55
Article

Case Study: Computing Black-Scholes with Intel® Advanced Vector Extensions

This case study discusses Intel® Advanced Vector Extensions (Intel® AVX) and gives an overview of the Black-Scholes valuation.
Authored by shuo-li (Intel) Last updated on 01/26/2017 - 00:49
Article

Case Study: Achieving High Performance on Monte Carlo European Option Using Stepwise Optimization Framework

Read this case study that discusses the Monte Carlo method of statistical computing to solve complex scientific computing problems.
Authored by shuo-li (Intel) Last updated on 01/26/2017 - 00:49
Article

Black-Scholes-Merton Formula on Intel® Xeon Phi™ Coprocessor

Get access to source code and test workloads, plus build directions for the Black-Scholes-Merton formula.
Authored by shuo-li (Intel) Last updated on 01/26/2017 - 00:49
Article

Monte Carlo Method for Stock Options Pricing Sample

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Authored by Vadim Kartoshkin (Intel) Last updated on 01/26/2017 - 00:49
Article

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 shuo-li (Intel) Last updated on 01/26/2017 - 00:49
Article

Data Layout Optimization Using SIMD Data Layout Templates

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 01/26/2017 - 00:49
Article

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 01/26/2017 - 00:49
Article

Intel® HPC Developer Conference 2016 - Session Presentations

The 2016 Intel® HPC Developer Conference brought together developers from around the world to discuss code modernization in high-performance computing.

Authored by Mike P. (Intel) Last updated on 01/26/2017 - 00:49
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