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Diagnostic 15527: loop was not vectorized: function call to xxx cannot be vectorized

Product Version: Intel(R) Visual Fortran Compiler XE 15.0 or a later version

Authored by Devorah H. (Intel) Last updated on 05/25/2018 - 15:30
Article

Using Intel® MKL and Intel® TBB in the same application

Intel MKL 11.3 has introduced Intel TBB support.

Authored by Gennady F. (Blackbelt) Last updated on 08/01/2019 - 09:22
Blog post

What is Thread Parallelism, and How Do I Put It to Use?

An Intro to Multi-Level Parallelism for High-Performance Computing by Clay Breshears | Life Sciences Software Architect, Intel
Authored by Clay B. (Blackbelt) Last updated on 12/12/2018 - 18:08
Blog post

Vectorized Reduction 2: Let the Compiler do that Voodoo that it do so well

As I mentioned in my previous post about writing a vectorized reduction code from Intel vector intrinsics, that part of the code was just the finishing touch on a loop computing squared difference of complex values.
Authored by Clay B. (Blackbelt) Last updated on 12/12/2018 - 18:08
Blog post

Big Datasets from Small Experiments

Authored by Andrey Vladimirov Last updated on 07/04/2019 - 18:46
Blog post

Brain Development Simulation, 300x Faster

Authored by Andrey Vladimirov Last updated on 07/04/2019 - 17:45
Article

Books - High Performance Parallelism Pearls

A look into the contents of the two "Pearls" books, edited by James Reinders and Jim Jeffers. These books contain a collection of examples of code modernization.
Authored by Mike P. (Intel) Last updated on 09/30/2019 - 17:30
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.
Authored by admin Last updated on 09/30/2019 - 17:28
Article

Case Study: BerkeleyGW using Intel® Xeon Phi™ Processors

BerkeleyGW is a Materials Science application for calculating the excited state properties of materials such as band gaps, band structures, absoprtion spectroscopy, photoemission spectroscopy and m

Authored by Mike P. (Intel) Last updated on 10/15/2019 - 15:30
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 10/15/2019 - 16:40