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.
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.
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.
使用基于英特尔® AI DevCloud 的英特尔® Optimization for TensorFlow 介绍英特尔® 至强® 可扩展处理器的架构和优化
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.
2017 年3 月15日，英特尔携手 MobileODT*（MobileODT* 公司致力于向全球每位女性普及宫颈癌筛选）在 Kaggle.com 网站推出人工智能竞赛。Kaggle 是知名的数据相关竞赛的领先平台，通过该平台，公司可以发布建模问题，专业人士、开发人员和研究人员以竞赛的形式提供最佳解决方案。
本文向人工智能 (AI) 社区介绍了在基于英特尔® 至强和英特尔® 至强融核™ 处理器的平台上实施的 TensorFlow* 优化。
Theano* is a Python* library developed at the LISA lab to define, optimize, and evaluate mathematical expressions, including the ones with multi-dimensional arrays. Theano can be installed and used with several combinations of development tools and libraries on a variety of platforms. This tutorial provides one such recipe describing steps to build and install Intel-optimized Theano with Intel®...