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.
作者: Michael Greenfield (Intel) 最后更新时间: 2019/07/06 - 16:40
博客

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).

作者: Sharmila C. (Intel) 最后更新时间: 2019/08/01 - 09:30
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.
作者: 最后更新时间: 2019/07/06 - 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.
作者: 最后更新时间: 2019/07/06 - 16:40
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.
作者: Neil V. (Intel) 最后更新时间: 2019/07/06 - 16:30
File Wrapper

Parallel Universe Magazine - Issue 27, January 2017

作者: 管理 最后更新时间: 2019/03/21 - 12:00
File Wrapper

Parallel Universe Magazine - Issue 28, April 2017

作者: 管理 最后更新时间: 2019/03/21 - 12:00
File Wrapper

Parallel Universe Magazine - Issue 31, January 2018

作者: 管理 最后更新时间: 2018/12/12 - 18:08
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*
作者: Nathan Greeneltch (Intel) 最后更新时间: 2019/07/31 - 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
作者: Nathan Greeneltch (Intel) 最后更新时间: 2019/08/09 - 02:02