Showing 13 open source projects for "gpu-z"

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    Bandicoot

    Bandicoot

    fast C++ library for GPU linear algebra & scientific computing

    * Fast GPU linear algebra library (matrix maths) for the C++ language, aiming towards a good balance between speed and ease of use * Provides high-level syntax and functionality deliberately similar to Matlab * Provides an API that is aiming to be compatible with Armadillo for easy transition between CPU and GPU linear algebra code * Useful for algorithm development directly in C++, or quick conversion of research code into production environments * Distributed under the permissive Apache...
    Downloads: 3 This Week
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  • 2
    PMCGPU

    PMCGPU

    Parallel simulators for Membrane Computing on the GPU

    Membrane Computing is a new research area (within Natural Computing) that aims to provide computing devices abstracted from the functioning and structure of living cells. These devices are called P systems. The objective of this project (PMCGPU) is to bring together all the researchers working on the development of parallel simulators for P systems, specially those using the GPU (e.g. CUDA, OpenCL, etc). Other parallel platforms are also welcome (multicore and manycore, FPGAs, etc...
    Downloads: 0 This Week
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  • 3
    FastFlow: programming multi-core

    FastFlow: programming multi-core

    Pattern-based multi/many-core parallel programming framework

    FastFlow is a C/C++ programming framework supporting the development of pattern-based parallel programs on multi/many-core, GPUs and distributed platforms. FastFlow run-time is built upon non-blocking threads and lock-free queues. Thanks to its very efficient CAS-free communication/synchronization support (e.g. few clock cycles core-to-core latency), FastFlow effectively supports the exploitation of fine grain parallelism, e.g. parallel codes managing very high frequency streams on...
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    Downloads: 2 This Week
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  • 4

    GTkNN

    GPU-based Textual kNN (GT-kNN)

    The following code is a parallel kNN implementation that uses GPUs for the high dimensional data in text classification. You can use it to classify documents using kNN or to generate meta-features based on the distances between a query document and its k nearest neigbors
    Downloads: 0 This Week
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    MXLib is a C++ wrapper around the Intel® Integrated Performance Primitives (IPP) library and NVidia NPP CUDA library. You can use either IPP code (or a subset of functions that do not require IPP) on the CPU side, or use NPP/CUDA on the GPU side, or use both together. The function syntax is similar to that found in MatLab and the library is designed to make it easy to port your code from MatLab to C++. The idea is to provide Scientists, Engineers, Researchers and other non full-time...
    Downloads: 1 This Week
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  • 6
    Genetic Programming in OpenCL is a parallel implementation of genetic programming targeted at heterogeneous devices, such as CPU and GPU. It is written in OpenCL, an open standard for portable parallel programming across many computing platforms.
    Downloads: 0 This Week
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  • 7

    PrimeCoin CPU & GPU Miners

    Application for PrimeCoin [XPM] mining

    This is an application for PrimeCoin [XPM] cryptocurrency mining. You can mine PrimeCoins with just CPU or your video card (GPU)[GPU mining isn't available at this moment]. Current pre-alpha for x86 and x64 CPUs is based on original jhPrimeminer by jh00, but uses my own HugeInteger library instead of original GMP lib.
    Downloads: 0 This Week
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  • 8

    GPU Interruptible Kernels

    Create CUDA kernels with unlimited variables and execution time

    Implementation of heavy computing tasks on GPU's faces two limits: 1) number of parameters/variables in each kernel; 2) computation time. This very simple C++ header allows to easily create CUDA kernels that overcome both limitations. The library adds a small overhead to the GPU kernels, but in carefully designed applications the slowdown should hardly be noticeable.
    Downloads: 0 This Week
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  • 9

    LBP in multiple platforms

    LBP implementation in multiple computing platforms (ARM,GPU, DSP...)

    ...: - OpenCL for CPU & GPU - OpenCL for GPU (branchless) - C code optimized for ARM - OpenGL ES 2.0 shaders mobile GPUs - C code for TI C64x DSP core (branchless) - C code for TTA processor synthesis If you use the code somewhere, please cite: Bordallo López M., Nieto A., Boutellier J., Hannuksela J., and Silvén O. "Evaluation of real-time LBP computing in multiple architectures," Journal of Real Time Image Processing, 2014
    Downloads: 0 This Week
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  • 10

    gpufsknn

    A GPU-based efficient data parallel formulation of the kNN problem

    A GPU-based efficient data parallel formulation of the k-Nearest Neighbor (kNN) search problem which is a popular method for classifying objects in several fields of research, such as- pattern recognition, machine learning, bioinformatics etc.
    Downloads: 0 This Week
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  • 11
    Porting of the core simulation portions of smoldyn to the GPU, using CUDA
    Downloads: 0 This Week
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  • 12
    A simple rendering, image processing engine. Includes a framework width (multiplatform) event handling, plugin management, a templated based math library and some exotic features like general linear camera, gpu based (OpenGL) image process...
    Downloads: 0 This Week
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  • 13
    We propose a novel algorithm for computing the number of ordered integer partitions with upper bounds. This problem's task is to compute the number of distributions of z balls into n urns with constrained capacities.
    Downloads: 0 This Week
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