Blog post

Optimizing Big Data processing with Haswell 256-bit Integer SIMD instructions

Big Data requires processing huge amounts of data. Intel Advanced Vector Extensions 2 (aka AVX2) promoted most Intel AVX 128-bits integer SIMD instruction sets to 256-bits.

Authored by gaston-hillar (Blackbelt) Last updated on 07/06/2019 - 17:00
Blog post

Intel® Data Analytics Acceleration Library

The Intel® Data Analytics Acceleration Library (Intel® DAAL) helps speed big data analytics by providing highly optimized algorithmic building blocks for all data analysis stages (Pre-processing, Transformation, Analysis, Modeling, Validation, and Decision Making) for offline, streaming and distributed analytics usages. It’s designed for use with popular data platforms including Hadoop*, Spark*,...
Authored by James R. (Blackbelt) Last updated on 12/12/2018 - 18:00
Article

Tutorial for Intel® DAAL: Using Simple C++ Examples

System Environment

Intel® DAAL version : 2016 Gold Initial Release (w_daal_2016.0.110.exe)

OS : Windows* 8.1

IDE : Visual Studio 2013

 

Authored by JON J K. (Intel) Last updated on 07/03/2019 - 10:17
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.
Authored by Gennady F. (Blackbelt) Last updated on 07/05/2019 - 14:54
Article

Open Source Project: Intel® Data Analytics Acceleration Library (Intel® DAAL)

Intel has created a data analytics acceleration project on github, to help accelerate data analytic

Authored by James R. (Blackbelt) Last updated on 05/30/2018 - 07:00
Article

Free access to Intel® Compilers, Performance libraries, Analysis tools and more...

Intel® Parallel Studio XE is a very popular product from Intel that includes the Intel® Compilers, Intel® Performance Libraries, tools for analysis, debugging and tuning, tools for MPI and the Intel® MPI Library. Did you know that some of these are available for free? Here is a guide to “what is available free” from the Intel Parallel Studio XE suites.
Authored by admin Last updated on 03/21/2019 - 12:00
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.
Authored by Andres Rodriguez (Intel) Last updated on 03/11/2019 - 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.
Authored by Last updated on 07/06/2019 - 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.

Authored by Vadim Pirogov (Intel) Last updated on 03/21/2019 - 12:00
Article

Running Intel® Parallel Studio XE Analysis Tools on Clusters with Slurm* / srun

Since HPC applications target high performance, users are interested in analyzing the runtime performance of such applications.

Authored by Michael Steyer (Intel) Last updated on 07/06/2019 - 11:23