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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 07/05/2019 - 19:13
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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
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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 07/06/2019 - 16:40
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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 07/06/2019 - 16:40
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Transform Enterprise, HPC & AI, Accelerate Parallel Code

Authored by admin Last updated on 07/06/2019 - 16:15
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英特尔® 处理器助力深度学习训练

2017 年 11 月 7 日,加州大学伯克利分校、德克萨斯大学和加州大学戴维斯分校的研究人员发表了他们的研究结果:在 CPU 上 31 分钟(截至发表时间)训练完 ResNet-50* 以及 11 分钟训练完 AlexNet*,使其达到一流的准确性,创造了纪录。这些结果均在英特尔® 至强® 可扩展处理器(之前代号为 Skylake-SP)上实现。
Authored by Andres Rodriguez (Intel) Last updated on 08/21/2018 - 18:52
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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