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Benefits of Intel® Optimized Caffe* in comparison with BVLC Caffe*

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Автор: JON J K. (Intel) Последнее обновление: 30.05.2018 - 07:00
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Parallel Universe Magazine - Issue 26, October 2016

Автор: админ Последнее обновление: 12.12.2018 - 18:08
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Track Reconstruction with Deep Learning at the CERN CMS Experiment

This blog post is part of a series that describes my summer school project at CERN openlab.

Автор: Последнее обновление: 30.09.2019 - 16:50
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Intel® CPU Excels in MLPerf* Reinforcement Learning Training

Today, MLPerf* consortium, a group of 40 companies and university research institutes, published the 2nd round of the benchmark results based upon ML

Автор: Koichi Yamada (Intel) Последнее обновление: 30.09.2019 - 16:50
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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.
Автор: Gennady F. (Blackbelt) Последнее обновление: 15.10.2019 - 16:50
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Celebrating a Decade of Parallel Programming with Intel® Threading Building Blocks (Intel® TBB)

This year marks the tenth anniversary of Intel® Threading Building Blocks (Intel® TBB).

Автор: Sharmila C. (Intel) Последнее обновление: 15.10.2019 - 18:16