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.
This article will describe performance considerations for CPU inference using Intel® Optimization for TensorFlow*
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.
This article explores what happens when Intel solutions support functional and logic programming languages that are regularly used for Artificial Intelligence (AI) and proposes a Prolog interpreter recompilation using Intel® C++ Compiler and libraries in order to evaluate their contribution to logic based AI.
The Seldon Core open source machine learning deployment platform facilitates management of inference pipelines
The computer learning code Caffe* has been optimized for Intel® Xeon Phi™ processors. This article provides detailed instructions on how to compile and run this Caffe* optimized for Intel® architecture to obtain the best performance on Intel Xeon Phi processors.