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应用蚁群优化算法 (ACO) 实施交通网络扩展

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 10/15/2019 - 16:40
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 10/15/2019 - 16:40
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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.
Authored by Last updated on 10/15/2019 - 16:50
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Maximize Performance of Intel® Software Optimization for PyTorch* on CPU

This article describes what you need to consider in order to get a satisfying performance with PyTorch, with examples.
Authored by Jing X. (Intel) Last updated on 02/02/2020 - 15:40
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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 10/15/2019 - 15:30
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Code Sample: Optimizing Binarized Neural Networks on Intel® Xeon® Scalable Processors

In the previous article, we discussed the performance and accuracy of Binarized Neural Networks (BNN). We also introduced a BNN coded from scratch in the Wolfram Language. The key component of this neural network is Matrix Multiplication.
Authored by Yash Akhauri Last updated on 10/15/2019 - 16:50
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Building and Probing Prolog* with 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.
Authored by Flavio Luis de Mello Last updated on 01/24/2018 - 15:35
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Accelerate Deep Learning Applications Using Multiprocessing and Intel® Math Kernel Library (Intel® MKL) for Deep Neural Networks

DarwinAI’s Generative Synthesis platform uses Artificial Intelligence to generate compact, highly efficient neural network models from existing model
Authored by admin Last updated on 11/20/2019 - 10:04
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Execution Analysis of Training a Deep Neural Network Task

High-performance computing (HPC) can be defined as the use of a set of techniques that enable the maximum performance of a processing platform.

Authored by admin Last updated on 12/12/2018 - 18:00