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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.
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    In continued efforts to optimize Deep Learning workloads on Intel® architecture, our engineers explore various paths leading to the maximum performance.

Criado por Gennady F. (Blackbelt) Última atualização em 21/03/2019 - 12:28
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为了不断优化英特尔® 架构的深度学习工作负载,我们的工程师探索不同的路径,以达到最高性能。

Criado por Gennady F. (Blackbelt) Última atualização em 21/03/2019 - 12:28
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Using Intel® MPI Library on Intel® Xeon Phi™ Product Family

This document is designed to help users get started writing code and running MPI applications using the Intel® MPI Library on a development platform that includes the Intel® Xeon Phi™ processor.
Criado por Nguyen, Loc Q (Intel) Última atualização em 21/03/2019 - 12:00