Set Up Intel® Software Optimization for Theano* and Supporting Tools

Get recipes for installing development tools and libraries on various platforms for the Python library.
作者: Sunny G. (Intel) 最后更新时间: 2018/05/08 - 10:50

Intel® Distribution for Python 2017 Update 2 accelerates five key areas for impressive performance gains

Intel Corporation is pleased to announce the release of Intel® Distribution for Python* 2017 Update 2, which offers both performance improvements and new features. 

作者: Sergey Maidanov (Intel) 最后更新时间: 2018/05/25 - 11:00

Intel® Math Kernel Library Improved Small Matrix Performance Using Just-in-Time (JIT) Code Generation for Matrix Multiplication (GEMM)

    The most commonly used and performance-critical Intel® Math Kernel Library (Intel® MKL) functions are the general matrix multiply (GEMM) functions.

作者: Gennady F. (Blackbelt) 最后更新时间: 2019/03/21 - 03:01

Second Generation Intel® Xeon® Processor Scalable Family Technical Overview

New features and enhancements available in the second generation Intel® Xeon® processor Scalable family and how developers can take advantage of them
作者: David Mulnix (Intel) 最后更新时间: 2019/09/30 - 17:28

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: 2019/10/15 - 15:30

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: 2019/10/15 - 15:30

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: 2019/10/15 - 16:40

Getting Started with Intel® Optimization for PyTorch* on Second Generation Intel® Xeon® Scalable Processors

Accelerate deep learning PyTorch* code on second generation Intel® Xeon® Scalable processor with Intel® Deep Learning Boost.
作者: Nathan Greeneltch (Intel) 最后更新时间: 2019/10/15 - 16:50

Intel Solutions and Technologies for the Evolving Data Center

  One Stop for Optimizing Your Data Center From AI to Big Data to HPC: End-to-end Solutions
作者: 管理 最后更新时间: 2019/10/15 - 17:00

Tencent* Uses Machine Learning for In-Game Purchase Recommendation System on Intel® Xeon® Processors

To enhance the online gaming user experience, Tencent uses an in-game purchase recommendation system employing the machine learning method to help users decide what equipment they would want to buy within their games. Tencent machine learning engine uses DGEMM6 extensively in its module to compute the coefficients for the logistic regression machine learning algorithm.
作者: Nguyen, Khang T (Intel) 最后更新时间: 2019/10/15 - 19:55