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Intel Vectorization Toolkit: 3. Determine Loop Candidates Using Intel Compiler Vec-Report

Intel Vectorization Toolkit: 3. Vectorization report for loop candidates
Autor AmandaS (Intel) Última actualización 25/05/2018 - 15:30
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Best Practices for Using Intel® Cilk™ Plus

Performance tuning of an existing application is truly a challenge and it depends on a lot of factors like the nature of algorithm the application works on, if the implementation is scalable

Autor Anoop M. (Intel) Última actualización 25/05/2018 - 15:30
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Improving Averaging Filter Performance Using Intel® Cilk™ Plus

Intel® Cilk™ Plus is an extension to the C and C++ languages to support data and task parallelism.  It provides three new keywords to i

Autor Anoop M. (Intel) Última actualización 12/12/2018 - 18:00
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Vectorizing Loops with Calls to User-Defined External Functions

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Autor Anoop M. (Intel) Última actualización 12/12/2018 - 18:00
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New optimizations for X86 in upcoming GCC 5.0

 

Autor Evgeny Stupachenko (Intel) Última actualización 24/01/2018 - 12:12
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Intel MKL 11.3 has introduced Intel TBB support.

Autor Gennady F. (Blackbelt) Última actualización 01/08/2019 - 09:22
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Celebrating a Decade of Parallel Programming with Intel® Threading Building Blocks (Intel® TBB)

This year marks the tenth anniversary of Intel® Threading Building Blocks (Intel® TBB).

Autor Sharmila C. (Intel) Última actualización 01/08/2019 - 09:30
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Big Datasets from Small Experiments

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Brain Development Simulation, 300x Faster

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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.

Autor Gennady F. (Blackbelt) Última actualización 21/03/2019 - 03:01