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.
Authored by Sunny G. (Intel) Last updated on 07/05/2019 - 19:10
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Parallel Universe Magazine - Issue 27, January 2017

Authored by admin Last updated on 03/21/2019 - 12:00
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

Transform Enterprise, HPC & AI, Accelerate Parallel Code

Authored by admin Last updated on 07/06/2019 - 16:15
Article

Intel® Processors for Deep Learning Training

On November 7, 2017, UC Berkeley, U-Texas, and UC Davis researchers published their results training ResNet-50* in a record time (as of the time of their publication) of 31 minutes and AlexNet* in a record time of 11 minutes on CPUs to state-of-the-art accuracy. These results were obtained on Intel® Xeon® Scalable processors (formerly codename Skylake-SP).
Authored by Andres Rodriguez (Intel) Last updated on 04/15/2018 - 23:05