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Machine Learning and Knowledge Reasoning Probing with Intel® Architecture

This article presents a performance test of Intel® tuning platform composed by Intel® processor, Intel® C++ Compiler XE and Intel® Math Kernel Library (Intel® MKL) applied to usual AI problems, with two existing approaches of artificial intelligence probed.
Автор: Flavio Luis de Mello Последнее обновление: 24.01.2018 - 15:35
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Track Reconstruction with Deep Learning at the CERN CMS Experiment

Connecting the Dots
Автор: Последнее обновление: 12.12.2018 - 18:00
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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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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.
Автор: Последнее обновление: 15.10.2019 - 15:30
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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.
Автор: Последнее обновление: 15.10.2019 - 16:50
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基于英特尔® 至强™ 处理器 E5 产品家族的多节点分布式内存系统上的 Caffe* 培训

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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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