Search Results for "cuda gpu"
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Showing 25 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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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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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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JDFTx
Joint Density Functional Theory
JDFTx is a plane-wave density functional theory code designed for electronic structure theory development. One prominent unique capability is the treatment of solvated electronic systems using joint density functional theory. Please see http://jdftx.org for download and compile instructions, tutorials, documentation and citation information. -
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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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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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DualSPHysics
C++/CUDA/OpenMP based Smoothed Particle Hydrodynamics (SPH) Solver
DualSPHysics is based on the Smoothed Particle Hydrodynamics method and can be downloaded from the official website (www.dual.sphysics.org). The code is developed to study free-surface flow phenomena where Eulerian methods can be difficult to apply, such as waves or impact of dam-breaks on off-shore structures. DualSPHysics is a set of C++, CUDA and Java codes based on the SPHysics FORTRAN project (www.sphysics.org) that are designed to deal with real-life engineering problems and are... -
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LightSpMV
lightweight GPU-based sparse matrix-vector multiplication (SpMV)
LightSpMV is a novel CUDA-compatible sparse matrix-vector multiplication (SpMv) algorithm using the standard compressed sparse row (CSR) storage format. We have evaluated LightSpMV using various sparse matrices and further compared it to the CSR-based SpMV subprograms in the state-of-the-art CUSP and cuSPARSE. Performance evaluation reveals that on a single Tesla K40c GPU, LightSpMV is superior to both CUSP and cuSPARSE, with a speedup of up to 2.60 and 2.63 over CUSP, and up to 1.93 and 1.79 over cuSPARSE for single and double precision, respectively. -
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CUDAlign
CUDAlign is a tool that aligns huge DNA sequences in CUDA capable GPUs
CUDAlign is a tool able to align pairwise DNA sequences of unrestricted size in CUDA GPUs, using the Smith-Waterman algorithm combined with Myers-Miller. It produces the optimal alignment of 1 million base sequences in 45 seconds using a GTX 560 Ti. Many optimizations are being developed for this software. Look at the following papers for detailed information: [1] Edans Sandes, Alba Melo. Retrieving Smith-Waterman Alignments with Optimizations for Megabase Biological Sequences using GPU. ... -
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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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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 programmers an easy to use, high performance library of functions.
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...***** You will find all future GeNN updates on GitHub at: https://github.com/genn-team/genn THIS PAGE WILL NO LONGER BE MAINTAINED! ==================================== GeNN is a GPU enhanced Neuronal Network simulation environment based on code generation for NVidia CUDA.
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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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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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DecGPU: CUDA-based Error Correction
The first distributed and parallel short-read error corrector on GPUs
DecGPU (Distributed Error correction on GPUs) is a parallel and distributed error correction algorithm for large-scale short read assembly. It is implemented using CUDA C++ and MPI, running on a GPU cluster. -
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CUDA-based Linear Openings
Fast opening with linear SE on CPU and GPU
Fast opening with linear SE on CPU and GPU using Bartovsky algorithm. Featuring console example application. -
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The CUDA wrapper library provides means for an efficient resource sharing and resource protection on multi-user GPU clusters.It implements the following functionality: 1) Virtualization of the physical GPU devices 2) Ensuring NUMA affinity for GPUs
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Matlab CUDA wrappers. This project was part of GPUmat, a Freeware GPU Toolbox for Matlab(R) (http://gp.you.org). This program is free software (GPL).
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Particular filter CUDA
Improvements of positioning algorithms using CUDA
Our project consist in porting positioning algorithms on a GPU. We will improve programs which are already working on CPU in order to make them compatible with the CUDA technology offered by Nvidia. The advantage of this technology is that it allows us to use massive multithreading and so make calculations go faster. Algorithms will be implemented in C++.
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