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Article

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*
Автор: Nathan Greeneltch (Intel) Последнее обновление: 31.07.2019 - 12:11
Article

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
Автор: Nathan Greeneltch (Intel) Последнее обновление: 09.08.2019 - 02:02
File Wrapper

Parallel Universe Magazine - Issue 28, April 2017

Автор: админ Последнее обновление: 30.09.2019 - 16:45
File Wrapper

Parallel Universe Magazine - Issue 27, January 2017

Автор: админ Последнее обновление: 01.10.2019 - 16:55
Article

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
Article

Vector API Developer Program for Java* Software

This article introduces Vector API to Java* developers. It shows how to start using the API in Java programs, and provides examples of vector algorithms. It provides step-by-step details on how to build the Vector API and build Java applications using it. It provides the location for downloadable binaries for Project Panama binaries.
Автор: Neil V. (Intel) Последнее обновление: 15.10.2019 - 15:30
Article

Migrating Applications from Knights Corner to Knights Landing Self-Boot Platforms

While there are many different programming models for the Intel® Xeon Phi™ coprocessor (code-named Knights Corner (KNC)), this paper lists the more prevalent KNC programming models and further discusses some of the necessary changes to port and optimize KNC models for the Intel® Xeon Phi™ processor x200 self-boot platform.
Автор: Michael Greenfield (Intel) Последнее обновление: 15.10.2019 - 16:40
Article

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