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Parallel Universe Magazine #12: Advanced Vectorization

This blog contains additional content for the article "Advanced Vectorization" from Parallel Universe #12:

作者: 最后更新时间: 2019/07/03 - 20:08
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BKMs on the use of the SIMD directive

We had an ask from one of the various "Birds of a Feather" meetings Intel® holds at venues such as at the Super Computing* (SC) and International Super Computing* (ISC) conferences.

作者: 最后更新时间: 2019/07/06 - 17:00
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Optimized Pseudo Random Number Generators with AVX2

Intel® Math Kernel Library includes powerful and versatile random number generators that have been optimized to take full advantage of Intel

作者: gaston-hillar (Blackbelt) 最后更新时间: 2019/07/06 - 17:00
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Optimizing Big Data processing with Haswell 256-bit Integer SIMD instructions

Big Data requires processing huge amounts of data. Intel Advanced Vector Extensions 2 (aka AVX2) promoted most Intel AVX 128-bits integer SIMD instruction sets to 256-bits.

作者: gaston-hillar (Blackbelt) 最后更新时间: 2019/07/06 - 17:00
Article

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....
作者: 最后更新时间: 2018/12/12 - 18:00
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Three Pieces of Advice for Code Modernization Success

What three code modernization techniques would I suggest to help a programmer improve the execution performance of her code? With too many specific things to choose from, these are three recommendations for any programmer anywhere and anytime.
作者: Clay B. (Blackbelt) 最后更新时间: 2018/12/12 - 18:08
Article

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.
作者: 最后更新时间: 2019/07/06 - 16:40
Article

Programação Vetorial e Paralela com amplificador Intel® VTune™

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

作者: 最后更新时间: 2018/12/12 - 18:00
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Big Datasets from Small Experiments

作者: Andrey Vladimirov 最后更新时间: 2019/07/04 - 18:46
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Brain Development Simulation, 300x Faster

作者: Andrey Vladimirov 最后更新时间: 2019/07/04 - 17:45