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Article

游戏行业的人工智能设计(第一部分)

The gaming industry has seen great strides in game complexity recently. Game developers are challenged to create increasingly compelling games. This series explores important Artificial Intelligence (AI) concepts and how to optimize them for multi-core.
Автор: админ Последнее обновление: 12.12.2018 - 18:00
Article

OpenCL 2.0 中的 GPU-Quicksort: 嵌套并行性和工作组扫描函数

简介
Автор: Robert I. (Intel) Последнее обновление: 31.05.2019 - 14:20
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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

Manage Deep Learning Networks with Caffe* Optimized for Intel® Architecture

How to optimize Caffe* for Intel® Architecture, train deep network models, and deploy networks.
Автор: Andres Rodriguez (Intel) Последнее обновление: 11.03.2019 - 13:17
Article

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

Intel® Data Analytics Acceleration Library (Intel® DAAL) is a software solution that offers building blocks covering all the stages of data analytics, from preprocessing to decision making. The beta version of Intel DAAL 2017 provides support for the Python* language.
Автор: Gennady F. (Blackbelt) Последнее обновление: 08.10.2018 - 03:42
Article

Recipe: Optimized Caffe* for Deep Learning on Intel® Xeon Phi™ processor x200

The computer learning code Caffe* has been optimized for Intel® Xeon Phi™ processors. This article provides detailed instructions on how to compile and run this Caffe* optimized for Intel® architecture to obtain the best performance on Intel Xeon Phi processors.
Автор: Vamsi Sripathi (Intel) Последнее обновление: 21.03.2019 - 12:40
Article

Caffe* Optimized for Intel® Architecture: Applying Modern Code Techniques

This paper demonstrates a special version of Caffe* — a deep learning framework originally developed by the Berkeley Vision and Learning Center (BVLC) — that is optimized for Intel® architecture.
Автор: Последнее обновление: 06.07.2019 - 16:40
Article

Set Up Intel® Software Optimization for Theano* and Supporting Tools

Get recipes for installing development tools and libraries on various platforms for the Python library.
Автор: Sunny G. (Intel) Последнее обновление: 08.05.2018 - 10:50
Article

Introducing DNN primitives in Intel® Math Kernel Library

Please notes: Deep Neural Network(DNN) component in MKL is deprecated since intel® MKL ​2019 and will be removed in the next intel® MKL Release.

Автор: Vadim Pirogov (Intel) Последнее обновление: 21.03.2019 - 12:00
Article

面向英特尔® 架构优化的 Caffe*:使用现代代码技巧

This paper demonstrates a special version of Caffe* — a deep learning framework originally developed by the Berkeley Vision and Learning Center (BVLC) — that is optimized for Intel® architecture.
Автор: Последнее обновление: 06.07.2019 - 16:40