Search Results for "cuda gpu"
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Showing 32 open source projects for "cuda gpu"
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XMRig
RandomX, KawPow, CryptoNight, AstroBWT and GhostRider unified miner
High performance, open-source, cross-platform RandomX, KawPow, CryptoNight, and AstroBWT CPU/GPU miner, RandomX benchmark, and stratum proxy. XMRig is a high-performance, open-source, cross-platform RandomX, KawPow, CryptoNight, and AstroBWT unified CPU/GPU miner and RandomX benchmark. Official binaries are available for Windows, Linux, macOS, and FreeBSD. The preferred way to configure the miner is the JSON config file as it is more flexible and human-friendly. The command-line interface... -
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Monte Carlo eXtreme (MCX)
Physically accurate and validated GPU ray-tracer
MCX is a GPU-accelerated, general-purpose, physically-accurate and feature-rich 3-D light transport simulator. It is one of the fastest simulators because it can use tens of thousands of GPU threads to simulate photons in parallel. -
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CIRT
CIRT - CUDA Interactive Ray Tracer
CIRT is an implementation of PRTP (Programmable Ray Tracing Pipeline). Mainly it is to be used as a ray-tracing equivalent of OpenGL. It allows the user to implement various ray-tracing related algorithms. -
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SAGECAL
GPU/MIC accelerated radio interferometric calibration program
SAGECal is a very fast, memory efficient and GPU accelerated radio interferometric calibration program. It can handle all source models including points, Gaussians and Shapelets. It can calibrate along hundreds of directions without running out of memory in almost real time. Intel Xeon Phi acceleration is also available. Distributed calibration using MPI and consensus optimization is enabled. Also tools to build/restore sky models are included. -
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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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Darknet
Convolutional Neural Networks
...With GPU acceleration via CUDA and OpenCV integration, it achieves high performance in image recognition tasks. Its simplicity, combined with powerful capabilities, has made Darknet one of the most influential projects in the computer vision community. -
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PMCGPU
Parallel simulators for Membrane Computing on the GPU
...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). This project has been initiated by the Research Group on Natural Computing (Department of Computer Science and Artificial Intelligence, University of Seville). PMCGPU was born inside the P-Lingua project, of the same research group. ... -
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GPU MrBayes implements MrBayes MC(3) on the GPU using CUDA. When using our program in your article, please cite our paper "Efficient Implementation of MrBayes on multi-GPU" (http://mbe.oxfordjournals.org/content/early/2013/03/14/molbev.mst043.abstract.html?papetoc).
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xmrMiner
A CUDA based miner for Monero
An optimized Monero miner designed to maximize GPU mining efficiency. -
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This project, initially developed at University College London, contains programs to perform rigid, affine and non-linear registration of nifti or analyse images. Two versions of the algorithms are included, a CPU- and a GPU- (using CUDA) based implementation.
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...The program can be invoked within MATLAB and any other scripting language. It can export the results in different formats including ASCII text “.txt” and MATLAB “.mat” format. The program can also utilize the power of GPU via CUDA. With a modern gaming card “NVidia GTX TITAN”, a speed increase of a factor of 100 times can be achieved. This makes NPP a powerful tool especially for simulating long waveguides.
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viewpix
A Landsat 8 scene viewer
...A 30m resolution gray scale scene is generated by Viewpix and is presented as band 12. Each Landsat 8 scene is roughly 190 X 180 kilometers. Viewpix was originally written as a simple platform to test GPU software on low end computer systems. 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. ... -
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The GPU-BH tree solver is a FLASH4 module to calculate the gravitational potential using a CUDA device.
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CUDA-Quicksort
CUDA-Quicksort: A GPU-based implementation of the quicksort algorithm
CUDA-quicksort is a GPU-based implementation of the quicksort algorithm. CUDA-quicksort is designed to exploit the power computing of modern NVIDIA GPUs. "Two GPU-based implementations of the quicksort were presented in literature: the GPU-quicksort, a compute-unified device architecture (CUDA) iterative implementation, and the CUDA dynamic parallel (CDP) quicksort, a recursive implementation provided by NVIDIA Corporation."[*]. ... -
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This project, developed at UCL London, provides code for tomographic reconstruction. NiftyRec is written in C and has Python and Matlab extensions. Computationally intensive functions have a GPU accelerated version based on CUDA.
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A GUI interface to a tool for generating SSBumps (Self Shadowed Bump Maps). Includes a CUDA GPU rendering extension.
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HIPAcc
Heterogeneous Image Processing Acceleration (HIPACC) Framework
HIPAcc development has moved to github: https://github.com/hipacc HIPAcc allows to design image processing kernels and algorithms in a domain-specific language (DSL). From this high-level description, low-level target code for GPU accelerators is generated using source-to-source translation. As back ends, the framework supports CUDA, OpenCL, and Renderscript. HIPAcc allows programmers to develop imaging applications while providing high productivity, flexibility and portability as well as competitive performance: the same algorithm description serves as basis for targeting different GPU accelerators and low-level languages. -
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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 some variables such as sigma in Canny and see the result in real-time. ... -
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aodv protocol on gpu IIIT Bangalore
Aodv protocol on gpu
The project is implemented as part of the CS-110 operating system course at IIIT Bangalore 2013. Aodv protocol is implemented on GPU using CUDA 4.0. A significant gain in execution time is observed when compared to CPU. Thus a simulator which uses GPU can be built on similar lines of NS2 if all the protocols can be parallelized and implemented on GPU. Guide: Prof Shrisha Rao srao@iiitb.ac.in Prof Poonacha P G poonacha.pg@iiitb.ac.in Students: Abhilash C S abhilash.gowder@iiitb.org Abhishek Varshney abhishek.varshney@iiitb.org Dilip S dilip.s@iiitb.org Navik Yogesh Laljibhai navik.yogeshlaljibhai@iiitb.org Pradyot H Adavi pradyot.h.adavi@iiitb.org -
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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. But you can compile the source code if you want. Instructions to compile the source code:... -
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A GPU memory test utility for NVIDIA and AMD GPUs using well established patterns from memtest86/memtest86+ as well as additional stress tests. The tests are designed to find hardware and soft errors. The code is written in CUDA and OpenCL.
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Rozkład temperatury w pomieszczeniach
Symulacja procesów cieplnych zachodzących w pomieszczeniach
...Piotr Fiertek Celem projektu jest stworzenie środowiska symulacyjnego dla procesów termicznych zachodzących w pomieszczeniach. Integralną jego częścią jest implementacja algorytmów obliczeniowych na procesorach graficznych GPU przy użyciu standardów CUDA oraz OpenCL. Innymi ważnymi elementami są graficzna wizualizacja wyników z wykorzystaniem biblioteki graficznej OpenGL oraz stworzenie interfejsu użytkownika umożliwiającego zmianę parametrów symulacji. -
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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. ... -
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Oree - Optimum Real-time Estimation of Events of Interaction: real-time reconstruction of photon interaction events in Gamma Cameras. Optionally making use of a CUDA enable GPU, Oree achieves reconstruction of over 1M events/sec.
