Search Results for "cuda gpu"
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Showing 22 open source projects for "cuda gpu"
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CUDA-Q
C++ and Python support for the CUDA Quantum programming model
CUDA-Q is an open-source platform for developing hybrid quantum-classical applications using a unified programming model across CPUs, GPUs, and quantum processing units. It provides a full toolchain that includes compilers, runtimes, and libraries for writing quantum programs in both C++ and Python. The platform is designed to be hardware-agnostic, allowing developers to run applications on different quantum backends or simulate them efficiently using GPU acceleration when physical quantum hardware is unavailable. ... -
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CUDA-QX
Accelerated libraries for quantum-classical computing built on CUDA-Q
CUDA-QX is a collection of accelerated libraries built on top of the CUDA-Q platform, designed to enable rapid development of hybrid quantum-classical applications. It extends the CUDA-Q programming model by providing optimized implementations of domain-specific quantum computing primitives and workflows. The libraries are intended to help researchers and developers leverage GPUs, CPUs, and quantum processing units together in a unified computational model. CUDA-QX focuses on key areas such... -
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HOOMD-blue
Molecular dynamics and Monte Carlo soft matter simulation on GPUs
HOOMD-blue is a Python-driven particle simulation engine for molecular dynamics and hard-particle Monte Carlo simulations. It was designed from the ground up for GPU acceleration, with a high-performance C++ and CUDA backend. The software is especially useful for nano-scale, colloidal, polymer, soft matter, and materials simulations. Its Python interface lets users build simulation and analysis workflows using familiar scientific Python tools. HOOMD-blue supports efficient parallel execution and has been used for large-scale GPU-based simulations. ... -
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PyTorch Geometric
Geometric deep learning extension library for PyTorch
...We have outsourced a lot of functionality of PyTorch Geometric to other packages, which needs to be additionally installed. These packages come with their own CPU and GPU kernel implementations based on C++/CUDA extensions. We do not recommend installation as root user on your system python. Please setup an Anaconda/Miniconda environment or create a Docker image. We provide pip wheels for all major OS/PyTorch/CUDA combinations. -
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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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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... -
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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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GPU3SNP
Exhaustive search for third order epistatic interactions using CUDA
GPU3SNP is a multi-GPU tool that exhaustively analyzes case-control datasets looking for 3-SNP combinations that present epistatic interaction. It provides a list with the combinations that have higher Mutual Information, which is used as measure for interaction. It is parallelized using CUDA and can exploit several GPUs in the same node/system. -
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cphcttoolbox
Cph CT Toolbox is a selection of Computed Tomography tools
Copenhagen Computed Tomography Toolbox is a collection of applications and libraries for flexible and efficient CT reconstruction. The toolbox apps generally take a set of projections (X-ray intensity measurements) and filter and back project them in order to recreate the image or volume that the projections represent. The project includes both mostly informative CPU implementations and highly efficient GPU implementations. Regular releases are hosted at the Python Package Index. -
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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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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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Accelerated Feature Extraction Tool
A fast GPU accelerated feature extraction software for speech analysis
A fast feature extraction software tool for speech analysis and processing. It incorporates standard MFCC, PLP, and TRAPS features. The tool is a specially designed to process very large audio data sets. It uses GPU acceleration if compatible GPU available (CUDA as weel as OpenCL, NVIDIA, AMD, and Intel GPUs are supported). CPU SSE intrinsic instruction set is used in cases where no compatible GPU present. The output files are stored in HTK format. The software is developed at Department of Cybernetics at University of West Bohemia in Pilsen. -
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FreDec
Parallelized FREquency DEComposer algorithm
...After selection of the initial frequency candidates, the algorithm passes through all their possible combinations and estimates their multi-frequency statistical significance. In the end, it prints out the set of largest frequency tuples that were still found significant. The GPU computing is implemented through CUDA and brings a significant performance increase. It is still possible to run FreDec solely on CPU, if no suitable GPU device is available in the system. See the details of the underlying theory in Baluev 2013, MNRAS, V. 436, P. 807 The description of the algorithm itself can be found in arXiv:1309.0100. ... -
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Molecular Measurer
Parallel, Stochastic Measurement of Molecular Surface Area
A program to measure molecular surface area. The algorithm is GPU-accelerated using CUDA and is described in the research paper linked from the project home page. The input to the program is xyzr files, which can be generated from pdb files. -
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birgHPCC
Rapid CUDA Cluster Deployment
...While retaining the major functions of the original birgHPC, including automated computing cluster conversion and auto slots detection, the new version (birgHPCC) is capable of creating and configuring a compute unified device architecture (CUDA) computing cluster, hence the extra “C” in the name. In addition to the increase in image size (less than 2 gigabytes) and a new Linux base (previously Debian, now Ubuntu), CUDA-capable bioinformatics software programs, such as NAMD, HOOMD-blue, VMD, GPU-HMMER and GPU-BLAST, are pre-installed in birgHPCC, along with the CUDA driver, libraries and software development kit (SDK). ... -
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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.
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simple game of life use gpu cuda
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This project shows how to integrate NVIDIA CUDA GPU programming API into ITK (Insight Segmentation and Registration Toolkit) library
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multiDAC is intended to become a user-friendly tool for image- and videoprocessing in the field of deformation/movement analysis. It is written in C# with some C routines using CPU/GPU parallelization (e.g. CUDA) and features a plugin manager.
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