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Parallel Universe Magazine - Issue 23, November 2015

Autor admin Última actualización 12/12/2018 - 18:08
Article

Whatever the Weather: The Intel Five Step Framework for Code Modernization

Weather forecasting is a crucial aspect of modern life, enabling efficient planning and logistics, while also protecting life and property through timely warnings of severe conditions. But accurate, long-range weather prediction is extremely complex, often involving enormous data sets and requiring code that is optimized to leverage the most advanced computer hardware features available.
Autor Última actualización 30/09/2019 - 17:30
Article

Vectorization Advisor 助您一臂之力

Vectorization Advisor is like having a trusted friend look over your code and give you advice based on what he sees. As you’ll see in this article, user feedback on the tool has included, “there are significant speedups produced by following advisor output, I'm already sold on this tool!”
Autor Última actualización 02/10/2019 - 15:40
Article

Get a Helping Hand from the Vectorization Advisor

Learn practical tips for using the vectorization advisor, which is part of Intel® Advisor.
Autor Última actualización 02/10/2019 - 15:41
Article

Case Study: Optimized Code for Neural Cell Simulations

One of the Intel® Modern Code Developer Challenge winners, Daniel Falguera, describes many of the optimizations he implemented and why some didn't work.
Autor Última actualización 03/10/2019 - 07:55
Article

案例研究: 面向神经细胞模拟优化代码

Intel held the Intel® Modern Code Developer Challenge that had about 2,000 students from 130 universities in 19 countries registered to participate in the Challenge. They were provided access to Intel® Xeon Phi™ coprocessors to optimize code used in a CERN openlab brain simulation research project. In this article Daniel Vea Falguera (Modern Code Developer Challenge winner) shares how he...
Autor Última actualización 03/10/2019 - 07:56
Article

基于英特尔® 架构加速金融应用

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Autor George Raskulinec (Intel) Última actualización 03/10/2019 - 08:00
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。

Autor Última actualización 03/10/2019 - 08:02
Article

Tencent* Uses Machine Learning for In-Game Purchase Recommendation System on Intel® Xeon® Processors

To enhance the online gaming user experience, Tencent uses an in-game purchase recommendation system employing the machine learning method to help users decide what equipment they would want to buy within their games. Tencent machine learning engine uses DGEMM6 extensively in its module to compute the coefficients for the logistic regression machine learning algorithm.
Autor Nguyen, Khang T (Intel) Última actualización 15/10/2019 - 19:55