Фильтры

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.
Автор: Gennady F. (Blackbelt) Последнее обновление: 05.07.2019 - 14:54
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).
Автор: Nguyen, Khang T (Intel) Последнее обновление: 06.07.2019 - 16:40
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

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

Improving Support Vector Machine with Intel® Data Analytics Acceleration Library

Introduction
Автор: Nguyen, Khang T (Intel) Последнее обновление: 07.10.2018 - 07:15
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
Видео

BigDL: Distributed Deep Learning on Apache Spark

BigDL is a distributed deep learning library for Apache Spark*; with BigDL, users can write their deep learning applications as standard Spark programs, which can directly run on top of existing Sp

Автор: Gerald M. (Intel) Последнее обновление: 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.
Автор: Bryan B. (Intel) Последнее обновление: 23.05.2018 - 11:00
Article

BigDL – Scale-out Deep Learning on Apache Spark* Cluster

Learn how to install and use BigDL for training and testing some of the commonly used deep neural network models on Apache Spark.
Автор: Sunny G. (Intel) Последнее обновление: 11.03.2019 - 13:17
Article

Distributed Deep Learning with Docker*, Intel® Nervana™ technology, neon™, and Pachyderm*

The recent advances in machine learning and artificial intelligence are amazing! It seems like we see something groundbreaking every day, from self-driving cars, to AIs learning complex games.

Автор: Daniel W. Последнее обновление: 08.06.2018 - 11:40