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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.
Authored by Gennady F. (Blackbelt) Last updated on 07/05/2019 - 14:54
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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.
Authored by Gennady F. (Blackbelt) Last updated on 07/05/2019 - 14:55
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Intel® Distribution for Python* versus Non-Optimized Python: Breast Cancer Classification

This case study compares the performance of Intel® Distribution for Python* to that of non-optimized Python using a breast cancer classification. This comparison was done using machine learning algorithms from the scikit-learn* package in Python.
Authored by admin Last updated on 12/12/2018 - 18:00
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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
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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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Maximize TensorFlow* Performance on CPU: Considerations and Recommendations for Inference Workloads

This article will describe performance considerations for CPU inference using Intel® Optimization for TensorFlow*
Authored by Nathan Greeneltch (Intel) Last updated on 07/31/2019 - 12:11
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最大限度提升 CPU 上的 TensorFlow* 性能:推理工作负载的注意事项和建议

本文将介绍使用面向 TensorFlow 的英特尔® 优化* 进行 CPU 推理的性能注意事项
Authored by Nathan Greeneltch (Intel) Last updated on 08/09/2019 - 02:02