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Introduction to OpenMP* on YouTube*

Tim Mattson (Intel) has authored an extensive series of excellent videos as in introduction to OpenMP*.

Автор: Mike P. (Intel) Последнее обновление: 04.07.2019 - 19:51
Article

Using Intel® MKL and Intel® TBB in the same application

Intel MKL 11.3 has introduced Intel TBB support.

Автор: Gennady F. (Blackbelt) Последнее обновление: 01.08.2019 - 09:22
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

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.
Автор: Gennady F. (Blackbelt) Последнее обновление: 05.07.2019 - 14:55
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

Hybrid Parallelism: A MiniFE* Case Study

This case study examines the situation where the problem decomposition is the same for threading as it is for Message Passing Interface* (MPI); that is, the threading parallelism is elevated to the same level as MPI parallelism.
Автор: David M. Последнее обновление: 06.07.2019 - 16:40
Article

面向英特尔® 架构优化的 Caffe*:使用现代代码技巧

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

Programação Vetorial e Paralela com amplificador Intel® VTune™

Eduardo H. M. Cruz, Matheus S. Serpa, Arthur M. Krause, Philippe O. A. Navaux

Автор: Последнее обновление: 12.12.2018 - 18:00
Article

Performance of Classic Matrix Multiplication Algorithm on Intel® Xeon Phi™ Processor System

Matrix multiplication (MM) of two matrices is one of the most fundamental operations in linear algebra. The algorithm for MM is very simple, it could be easily implemented in any programming language. This paper shows that performance significantly improves when different optimization techniques are applied.
Автор: Последнее обновление: 14.06.2019 - 11:50
Блоги

Big Datasets from Small Experiments

Автор: Andrey Vladimirov Последнее обновление: 04.07.2019 - 18:46