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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

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
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.
Criado por Última atualização em 06/07/2019 - 16:40
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.

Criado por Vadim Pirogov (Intel) Última atualização em 21/03/2019 - 12:00
Article

针对英特尔® 至强™ 处理器 E5 系列的 Caffe* 评分优化

为了不断优化英特尔® 架构的深度学习工作负载,我们的工程师探索不同的路径,以达到最高性能。

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

Intel® Math Kernel Library for Deep Learning Networks: Part 1–Overview and Installation

Learn how to install and build the library components of the Intel MKL for Deep Neural Networks.
Criado por Bryan B. (Intel) Última atualização em 11/03/2019 - 13:17
Article

Intel® Math Kernel Library for Deep Neural Networks: Part 2 – Code Build and Walkthrough

Learn how to configure the Eclipse* IDE to build the C++ code sample, along with a code walkthrough based on the AlexNet deep learning topology for AI applications.
Criado por Bryan B. (Intel) Última atualização em 23/05/2018 - 11:00