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OpenMP* SIMD for Inclusive/Exclusive Scans

The Intel® C++ Compiler 19.0 and the Intel® Fortran Compiler 19.1 support the OpenMP* SIMD SCAN feature for inclusive and exclusive scans.
Authored by Varsha M. (Intel) Last updated on 07/23/2019 - 09:16
Documentation

Intel® C++ Compiler Code Samples from Intel® C++ Compiler Code Samples

Intel® Cilk™ Plus has been deprecated in the Intel® C++ Compiler 18.0. Prefer to use OpenMP-based syntax for offloading to the processor graphics.

Last updated on 03/21/2019 - 09:08
Article

Using Tasks Instead of Threads

Tasks are a lightweight alternative to threads that provide faster startup and shutdown times, better load balancing, an efficient use of available resources, and a higher level of abstraction.
Authored by admin Last updated on 07/05/2019 - 09:41
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Virtual Vector Function Supported in Intel® C++ Compiler 17.0

Intel® C++ Compiler 17.0 starts supporting virtual vector functions.

Authored by Chen, Yuan (Intel) Last updated on 06/01/2017 - 11:32
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Multi-core Intermediate

Introduction
Authored by Nguyen, Khang T (Intel) Last updated on 07/13/2018 - 17:29
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Explicit Vector Programming in Fortran

No longer does Moore’s Law result in higher frequencies and improved scalar application performance; instead, higher transistor counts lead to increased parallelism, both through more cores and thr

Authored by Martyn Corden (Intel) Last updated on 03/27/2019 - 15:50
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Benefits of Intel® Optimized Caffe* in comparison with BVLC Caffe*

Overview
Authored by JON J K. (Intel) Last updated on 05/30/2018 - 07:00
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Large Matrix Operations with SciPy* and NumPy*: Tips and Best Practices

Introduction
Authored by Last updated on 07/06/2019 - 22:04
Blog post

Unleash the Parallel Performance of Python* Programs

[updated 10/5/2018]

Authored by Anton Malakhov (Intel) Last updated on 10/05/2018 - 18:24
Article

Putting Your Data and Code in Order: Data and layout - Part 2

Apply the concepts of parallelism and distributed memory computing to your code to improve software performance. This paper expands on concepts discussed in Part 1, to consider parallelism, both vectorization (single instruction multiple data SIMD) as well as shared memory parallelism (threading), and distributed memory computing.
Authored by David M. Last updated on 07/06/2019 - 16:40