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OpenMP* and the Intel® IPP Library

How to configure OpenMP in the Intel IPP library to maximize multi-threaded performance of the Intel IPP primitives.
Authored by Last updated on 07/31/2019 - 14:30
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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

Authored by Anoop M. (Intel) Last updated on 12/12/2018 - 18:00
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Vectorizing Loops with Calls to User-Defined External Functions

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Authored by Anoop M. (Intel) Last updated on 12/12/2018 - 18:00
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Fast Gathering-based SpMxV for Linear Feature Extraction

This algorithm can be used to improve sparse matrix-vector and matrix-matrix multiplication in any numerical computation. As we know, there are lots of applications involving semi-sparse matrix computation in High Performance Computing. Additionally, in popular perceptual computing low-level engines, especially speech and facial recognition, semi-sparse matrices are found to be very common....
Authored by Last updated on 12/12/2018 - 18:00
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Programação Vetorial e Paralela com amplificador Intel® VTune™

Eduardo H. M. Cruz, Matheus S. Serpa, Arthur M. Krause, Philippe O. A. Navaux

Authored by Last updated on 12/12/2018 - 18:00
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Programming for Multicore and Many-core Products including Intel® Xeon® processors and Intel® Xeon Phi™ X100 Product Family coprocessors

The programming models in use today, used for multicore processors every day, are available for many-core coprocessors as well. Therefore, explaining how to program both Intel Xeon processors and Intel Xeon Phi coprocessor is best done by explaining the options for parallel programming. This paper provides the foundation for understanding how multicore processors and many-core coprocessors are...
Authored by James R. (Blackbelt) Last updated on 10/15/2019 - 15:11
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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.
Authored by Last updated on 10/15/2019 - 15:30
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面向英特尔® 架构优化的 Caffe*:使用现代代码技巧

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.
Authored by Last updated on 10/15/2019 - 16:50
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Intel® AVX-512 Instructions

The latest Intel® Architecture Instruction Set Extensions Programming Reference includes the definition of Intel® Advanced Vector Extensions 512 (Intel® AV

Authored by James R. (Blackbelt) Last updated on 10/15/2019 - 20:39
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Building FreeFEM++ with Intel® Software Tools for Developers

FreeFEM++ is a package that targeted for researchers who needs a powerful tool for solving partial differential equations.

Authored by Dmitry S. (Intel) Last updated on 10/15/2019 - 21:24