Фильтры

Article

How to Install the Python* Version of Intel® Data Analytics Acceleration Library (Intel® DAAL) in Linux*

The Intel® Data Analytics Acceleration Library (Intel® DAAL) 1, 2 is a software solution for data analytics. It provides building blocks for data preprocessing, transformation, modeling, predicting, and so on.
Автор: Nguyen, Khang T (Intel) Последнее обновление: 05.07.2019 - 19:05
Блоги

Celebrating a Decade of Parallel Programming with Intel® Threading Building Blocks (Intel® TBB)

This year marks the tenth anniversary of Intel® Threading Building Blocks (Intel® TBB).

Автор: Sharmila C. (Intel) Последнее обновление: 01.08.2019 - 09:30
Article

Scale-Up Implementation of a Transportation Network Using Ant Colony Optimization (ACO)

In this article an OpenMP* based implementation of the Ant Colony Optimization algorithm was analyzed for bottlenecks with Intel® VTune™ Amplifier XE 2016 together with improvements using hybrid MPI-OpenMP and Intel® Threading Building Blocks were introduced to achieve efficient scaling across a four-socket Intel® Xeon® processor E7-8890 v4 processor-based system.
Автор: Sunny G. (Intel) Последнее обновление: 05.07.2019 - 19:10
Article

应用蚁群优化算法 (ACO) 实施交通网络扩展

In this article an OpenMP* based implementation of the Ant Colony Optimization algorithm was analyzed for bottlenecks with Intel® VTune™ Amplifier XE 2016 together with improvements using hybrid MPI-OpenMP and Intel® Threading Building Blocks were introduced to achieve efficient scaling across a four-socket Intel® Xeon® processor E7-8890 v4 processor-based system.
Автор: Sunny G. (Intel) Последнее обновление: 05.07.2019 - 19:13
Article

如何在 Linux* 中安装英特尔® 数据分析加速库(英特尔® DAAL)的 Python* 版本

英特尔® 数据分析加速库(英特尔® DAAL) 1, 2 是一款用于数据分析的软件解决方案。它提供用于数据预处理、转换、建模和预测等任务的构建模块。
Автор: Nguyen, Khang T (Intel) Последнее обновление: 05.07.2019 - 19:06
File Wrapper

Parallel Universe Magazine - Issue 26, October 2016

Автор: админ Последнее обновление: 12.12.2018 - 18:08
Article

Intel® Math Kernel Library Improved Small Matrix Performance Using Just-in-Time (JIT) Code Generation for Matrix Multiplication (GEMM)

    The most commonly used and performance-critical Intel® Math Kernel Library (Intel® MKL) functions are the general matrix multiply (GEMM) functions.

Автор: Gennady F. (Blackbelt) Последнее обновление: 21.03.2019 - 03:01