Search Results for "linux nvidia"
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Showing 13 open source projects for "linux nvidia"
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ExCon Imager
Gigapixel GPU accelerated radio interferometric imager
ExCon can create images with a very wide field of view (more than billion pixels). It implements novel gridding and image weighting algorithms. It is well suited to make ultra deep radio interferometric images, minimizing aliasing artefacts and PSF variation. NVIDIA GPU acceleration is available. JAVA/SCALA support available. -
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GSvit
Fast FDTD solver with graphics card support
Fast FDTD solver with graphics card support. Optimized for nanoscale optics - scanning near field optical microscopy, rough surface scattering and solar cells. Uses CUDA environment for graphics card operation. -
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CUDALucas
A program that uses CUDA to accelerate the Lucas Lehmer test.
CUDALucas is a program implementing the Lucas-Lehmer primality test for Mersenne numbers using the Fast Fourier Transform implemented by nVidia's cuFFT library. You need a CUDA-capable nVidia card with compute compatibility >= 1.3 up to CUDA 6.5, 2.x up to 7.0 and 3.x for >=CUDA 8.0 . The program is run from the command line, however it can be configured without using a terminal. See the Wiki for more details. README for new users available at the Files/Downloads page. -
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CUDASW++: Smith-Waterman Algorithm
The fastest Smith-Waterman protein database search algorithm on GPUs
CUDASW++ software is a public open source software for Smith-Waterman protein database searches on Graphics Processing Units with CUDA. This software have been added to the NVIDIA Tesla Bio Workbench (http://www.nvidia.com/object/swplusplus_on_tesla.html -
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viewpix
A Landsat 8 scene viewer
...This is the "lite" version of Viewpix as it has no cuda filters installed. Viewpix is written in C. It is tested on Ubuntu and Centos. It should work with most current Linux distributions. Viewpix runs efficiently on computers with modest CPU's such as low power mini-ITX boards. It is known to work nicely on Intel NUC, AMD A6 SOC , and NVIDIA TX2. A multiple core cpu, 8 GB ram, and a large capacity hard drive are suggested. -
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Barracuda is a high-speed sequence aligner based on Sanger's BWA and utilizes the latest Nvidia CUDA architecture for accelerating alignments of sequence reads generated by next-generation sequencers.
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GPU Edge Detector
GPU Interactive Program For Edge detection
This is a standalone, all in one Edge Detector that is mainly running on GPU using the CUDA technology. Each algorithm also has an OpenCV counterpart which is the closest one in terms of speed. This project is partly based on the Sobel Filter sample available as part of the CUDA SDK. This project also partly uses the OpenCV library to load different types of image. This program includes: Prewitt filter, Roberts Cross, Canny edge detector and finally Sobel filter with the ability to modify... -
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GPUmat
GPUmat is a C/C++ GPU engine for Matlab based on NVIDIA CUDA.
Please download Windows and Linux version by clicking on "Browse All Files". GPUmat allows standard MATLAB code to run on GPUs. The engine is written in C/C++ and based on NVIDIA CUDA. Please contact gpyougroup@gmail.com for any questions. Unfortunately GPUmat was compiled for CUDA 5.0 and we basically stopped any support for other CUDA version because we don't have the resources to do it. -
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CUDA-SPHERE-FWD-MEEG
CUDA accelerated spherical model forward solution for EEG/MEG
CUDA-SPHERE-FWD-MEEG is a CUDA C based toolkit which provides a GPU based implementation of the spherical model forward solution for the 306 channel Elekta Neuromag MEG system and the EEG. The 1-Sphere forward solution for the MEG and the 4-Sphere forward solution for the EEG is implemented in CUDA C and an accelerated solution is obtained using the NVIDIA GPU when the solution is calculated for a large number of dipoles (on the order of 15000 and above) and sensor locations. Speedup by a... -
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A way to program NVIDIA graphical processors, from Fortran-9X and eventually Matlab. Project documentation at http://flagon.wiki.sourceforge.net/
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All pairs n-body simulation of electromagnetic forces on charged particles, adapted from Nvidia SDK 3.2 sample. Uses Lorentz force from EM fields via the Biot-Savart law for moving charged particles (uses relative velocity). Relativistic.
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Using the CUDA API this project modifies the AutoDock software to run in parallel on NVIDIA GPUs. Users will be able to download and compile the code and use AutoDock on CUDA capable Graphics Cards. Autodock is located at http://autodock.scripps.edu/
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A fast parallel error correction tool for short reads. This software have been added to the NVIDIA Tesla Bio Workbench (http://www.nvidia.com/object/ec_on_tesla.html)
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