Search Results for "intel"
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Showing 6 open source projects for "intel"
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Armadillo
fast C++ library for linear algebra & scientific computing
* Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads: http://arma.sourceforge.net/download.html * Documentation: http://arma.sourceforge.net/docs.html * Bug reports: http://arma.sourceforge.net/faq.html * Git repo: https://gitlab.com/conradsnicta/armadillo-code -
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Real-ESRGAN ncnn Vulkan
NCNN implementation of Real-ESRGAN
...It provides command-line tools for upscaling images with selected models, allowing users to specify input/output paths, scaling factors, tile sizes, and model names from a compressed model set, which is particularly helpful for larger images or automated workflows. The Vulkan backend enables fast execution on GPUs from different vendors (Intel/AMD/Nvidia) with broad support, making it suitable for non-Python environments, production systems, or performance-constrained setups. -
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Java classes that enable definition of new Charsets based on other existing Charsets, without additional programming. Includes a character set with Kamenik encoding.
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JKalman is an Open Source Java implementation of Kalman filter. Kalman filter is an efficient computational (recursive) tool to estimate the dynamic state of a process in a way that minimizes the mean of error.
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A portable C++ library of multi-threaded STL algorithms (transform, accumulate...) using standard containers and iostreams. Thread, mutex, spinlock are templatized. Close to Intel Threading Building Blocks, HPC++ or PSTL. Idea of A.Stepanov and M.Austen.
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This distribution contains a novel fast CRC generation algorithm developed by Intel. This algorithm runs at under 3 cycles per byte (vs. 7) and thus triples the performance of existing CRC implementations. Slicing-by-8 uses an 8KB cache footprint.
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