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Article

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.
Автор: Sunny G. (Intel) Последнее обновление: 08.05.2018 - 10:50
Article

安装英特尔® Theano*软件优化包和支持工具

Theano* is a Python* library developed at the LISA lab to define, optimize, and evaluate mathematical expressions, including the ones with multi-dimensional arrays. Theano can be installed and used with several combinations of development tools and libraries on a variety of platforms. This tutorial provides one such recipe describing steps to build and install Intel-optimized Theano with Intel®...
Автор: Sunny G. (Intel) Последнее обновление: 08.05.2018 - 10:50
Article

Open Source Project: Intel® Data Analytics Acceleration Library (Intel® DAAL)

Intel has created a data analytics acceleration project on github, to help accelerate data analytic

Автор: James R. (Blackbelt) Последнее обновление: 27.08.2019 - 13:50
Article

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
Автор: David Mulnix (Intel) Последнее обновление: 30.09.2019 - 17:28
Article

CPUs are set to dominate high end visualization

Автор: James R. (Blackbelt) Последнее обновление: 30.09.2019 - 17:28
Article

Free access to Intel® Compilers, Performance libraries, Analysis tools and more...

Intel® Parallel Studio XE is a very popular product from Intel that includes the Intel® Compilers, Intel® Performance Libraries, tools for analysis, debugging and tuning, tools for MPI and the Intel® MPI Library. Did you know that some of these are available for free? Here is a guide to “what is available free” from the Intel Parallel Studio XE suites.
Автор: админ Последнее обновление: 30.09.2019 - 17:28
Article

Performance Gains for Ayasdi Analytics* on the Intel® Xeon® Processor E7-8890 V3

Ayasdi deploys vertical applications that utilize Topological Data Analysis to extract value from large and complex data. The Ayasdi platform incorporates statistical, geometric, and machine-learning methods through a topological framework to more precisely segment populations, detect anomalies, and extract features. This paper describes how Ayasdi’s Analytics* running on systems equipped with...
Автор: Nguyen, Khang T (Intel) Последнее обновление: 01.10.2019 - 16:44
Article

A Mission-Critical Big Data Platform for the Real-Time Enterprise

As the volume and velocity of enterprise data continue to grow, extracting high-value insight is becoming more challenging and more important. Businesses that can analyze fresh operational data instantly—without the delays of traditional data warehouses and data marts—can make the right decisions faster to deliver better outcomes.
Автор: Nguyen, Khang T (Intel) Последнее обновление: 01.10.2019 - 16:49
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