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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.
作者: 管理 最后更新时间: 2018/12/12 - 18:00
Article

游戏行业的人工智能设计(第二部分)

Designing AI for Games. Intelligent agents need to identify points of interest in the game world. This article shows how to identify and optimize points of interest and provides ways of organizing them for multi-threading.
作者: 管理 最后更新时间: 2018/12/12 - 18:00
Article

Создание искусственного интеллекта для игр (часть 1)

Автор: Дональд Кихо (Donald Kehoe)

作者: ALEXEY K. (Intel) 最后更新时间: 2018/12/12 - 18:00
Article

Создание искусственного интеллекта для игр (часть 2)

Восприятие и поиск путей
作者: ALEXEY K. (Intel) 最后更新时间: 2018/12/12 - 18:00
Article

Caffe* Training on Multi-node Distributed-memory Systems Based on Intel® Xeon® Processor E5 Family

Caffe is a deep learning framework developed by the Berkeley Vision and Learning Center (BVLC) and one of the most popular community frameworks for image recognition. Caffe is often used as a benchmark together with AlexNet*, a neural network topology for image recognition, and ImageNet*, a database of labeled images.
作者: Gennady F. (Blackbelt) 最后更新时间: 2019/07/05 - 14:54
Article

IDF'15 Webcast: Data Analytics and Machine Learning

This Technology Insight will demonstrate how to optimize data analytics and machine learning workloads for Intel® Architecture based data center platforms. Speaker: Pradeep Dubey Intel Fellow, Intel Labs Director, Parallel Computing Lab, Intel Corporation
作者: Mike P. (Intel) 最后更新时间: 2019/07/06 - 16:40
Article

基于英特尔® 至强™ 处理器 E5 产品家族的多节点分布式内存系统上的 Caffe* 培训

Caffe is a deep learning framework developed by the Berkeley Vision and Learning Center (BVLC) and one of the most popular community frameworks for image recognition. Caffe is often used as a benchmark together with AlexNet*, a neural network topology for image recognition, and ImageNet*, a database of labeled images.
作者: Gennady F. (Blackbelt) 最后更新时间: 2019/07/05 - 14:55
Article

Migrating Applications from Knights Corner to Knights Landing Self-Boot Platforms

While there are many different programming models for the Intel® Xeon Phi™ coprocessor (code-named Knights Corner (KNC)), this paper lists the more prevalent KNC programming models and further discusses some of the necessary changes to port and optimize KNC models for the Intel® Xeon Phi™ processor x200 self-boot platform.
作者: Michael Greenfield (Intel) 最后更新时间: 2019/07/06 - 16:40
博客

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).

作者: Sharmila C. (Intel) 最后更新时间: 2019/08/01 - 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.
作者: Sunny G. (Intel) 最后更新时间: 2019/07/05 - 19:10