Intel® Parallel Studio XE

Installing Intel Parallel Studio XE on AWS Linux Instances

Introduction

This article covers the installation steps with troubleshooting and tips for Intel® Parallel Studio XE on Amazon Web Services* (AWS*). Note that some of the tools may have functional restrictions due to the cloud environment.  For system requirements, please see Release Notes for details. For further Intel related support, visit https://software.intel.com/support.

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  • Building and Probing Prolog* with Intel® Architecture

    This article explores what happens when Intel solutions support functional and logic programming languages that are regularly used for Artificial Intelligence (AI) and proposes a Prolog interpreter recompilation using Intel® C++ Compiler and libraries in order to evaluate their contribution to logic based AI.
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  • How to use the Intel® Advisor Python API

    Introduction

    You can now access the Intel® Advisor database using our new Python API. We have provided several reference examples on how to use this new functionality. The API provides a flexible way to report on useful program metrics (Over 500 metric elements can be displayed). This article will describe how to use this new functionality.

    Getting started

    To get started, you first need to setup the Intel Advisor environment.

    > source advixe-vars.sh

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  • New Issue of The Parallel Universe is Here: Tuning Autonomous Driving Using Intel® System Studio

    Everything old is new again, and that’s just fine with us.

    We hope you’ll agree after you read the latest issue of The Parallel Universe, Intel’s quarterly magazine for developers. In this issue, we take a fresh look at what’s come before (OpenMP, MySQL*, Intel® C++ Compiler, vectorization) while looking ahead (autonomous driving applications, edge-to-cloud data compression, the latest programming languages).

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  • Intel® Parallel Studio XE Cluster Edition
  • Intel® Parallel Studio XE Composer Edition
  • Intel® Parallel Studio XE Professional Edition
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  • Automated Driving
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  • Profiling Tensorflow* workloads with Intel® VTune™ Amplifier

    Machine learning applications are very compute intensive by their nature. That is why optimization for performance is quite important for them. One of the most popular libraries, Tensorflow*, already has an embedded timeline feature that helps understand which parts of the computational graph are causing bottlenecks but it lacks some advanced features like an architectural analysis.

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  • Installing Intel Parallel Studio XE on AWS Windows Instances

    Introduction

    This article covers the installation steps with troubleshooting and tips for Intel® Parallel Studio XE on Amazon Web Services* (AWS*). Note that some of the tools may have functional restrictions due to the cloud environment.  For system requirements, please see Release Notes for details. For further Intel related support, visit https://software.intel.com/support.

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  • Intel Parallel Studio XE Evaluation Guide

    System Requirements and Prerequisites

    To ensure successful installation, please review the release notes and verify that your system has the capability, capacity and prerequisites to install the product.

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  • How F5 Networks Profiles for Success

    When Seattle-based F5 Networks, Inc. needed to amp up its BIG-IP DNS* solution for developers, it got help from Intel.

    Business users expect their applications to be fast, secure, and always available. Anything less is unacceptable. That’s why F5 gives the developers who build those applications the tools they need to deliver maximum speed, security, and availability.

  • Intel® Parallel Studio XE
  • Intel® Parallel Studio XE Cluster Edition
  • Intel® Parallel Studio XE Composer Edition
  • Intel® Parallel Studio XE Professional Edition
  • Intel® VTune™ Amplifier
  • Novosibirsk State University Gets More Efficient Numerical Simulation

    Russia's Novosibirsk State University boosted a simulation tool’s performance by 3X with Intel® Parallel Studio, Intel® Advisor, and Intel® Trace Analyzer and Collector, cutting the standard time for calculating one problem from one week to just two days.

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