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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.

Автор: Gennady F. (Blackbelt) Последнее обновление: 21.03.2019 - 12:28
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

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.
Автор: Nguyen, Khang T (Intel) Последнее обновление: 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.
Автор: Sunny G. (Intel) Последнее обновление: 05.07.2019 - 19:10
Article

Stanford HPC Center Summer Speaker Series: Introduction to High Performance Computing Tools

Автор: Mike P. (Intel) Последнее обновление: 21.03.2019 - 15:50
Article

How to Install the Python* Version of Intel® Data Analytics Acceleration Library (Intel® DAAL)

Intel® Data Analytics Acceleration Library (Intel® DAAL) is a software solution that offers building blocks covering all the stages of data analytics, from preprocessing to decision making. The beta version of Intel DAAL 2017 provides support for the Python* language.
Автор: Gennady F. (Blackbelt) Последнее обновление: 08.10.2018 - 03:42
Блоги

How Intel® Xeon Phi™ Processors Benefit Machine Learning/Deep Learning Apps and Frameworks

Machine learning can take very large amounts of data to predict possible outcomes with a high degree of accuracy. The second-generation Intel® Xeon Phi processor has the processor performance and memory bandwidth to address complex machine learning applications.
Автор: Pradeep Dubey (Intel) Последнее обновление: 21.03.2019 - 12:40
Видео

Looking at Machine Learning in Games

George Doubler (CTO, IBM Interactive Media) explores how Machine Learning platforms (like IBM's Watson or Google's initiatives) are just now starting to make their way into games.

Автор: админ Последнее обновление: 31.12.2018 - 14:00
Блоги

IDF16: Intel® Software Recap

Software, Networking and IoT Create “Best of All Worlds” at Intel Developer Forum 2016
Автор: Последнее обновление: 19.06.2019 - 16:21
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