Filtros

Página de destino responsiva

课程:机器人深度学习 | 英特尔® 人工智能开发人员计划

了解在许多机器人工作负载中使用深度学习算法的基础知识。
Criado por David C. (Intel) Última atualização em 16/08/2019 - 15:41
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.
Criado por Gennady F. (Blackbelt) Última atualização em 05/07/2019 - 14:54
Article

Caffe* Scoring Optimization for Intel® Xeon® Processor E5 Series

    In continued efforts to optimize Deep Learning workloads on Intel® architecture, our engineers explore various paths leading to the maximum performance.

Criado por Gennady F. (Blackbelt) Última atualização em 21/03/2019 - 12:28
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.
Criado por Gennady F. (Blackbelt) Última atualização em 05/07/2019 - 14:55
Article

Performance Comparison of OpenBLAS* and Intel® Math Kernel Library in R

Today, scientific and business industries collect large amounts of data, analyze them, and make decisions based on the outcome of the analysis. This paper compares the performance of Basic Linear Algebra Subprograms (BLAS), libraries OpenBLAS, and the Intel® Math Kernel Library (Intel® MKL).
Criado por Nguyen, Khang T (Intel) Última atualização em 06/07/2019 - 16:40
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.
Criado por Michael Greenfield (Intel) Última atualização em 06/07/2019 - 16:40
Article

Baidu Deep Neural Network Click-Through Rate on Intel® Xeon® Processors E5 v4

How do new web sites selling products or services appear at the top of the search list? The key is to use the right keywords that people might use to search for their products or services. Baidu1 is the most popular search engine in China. Ad companies can pay Baidu so that their ads appear at the top of the search list.
Criado por Nguyen, Khang T (Intel) Última atualização em 05/07/2019 - 14:36
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.
Criado por Sunny G. (Intel) Última atualização em 05/07/2019 - 19:10
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.
Criado por Andres Rodriguez (Intel) Última atualização em 11/03/2019 - 13:17