Search Results for "gpu processing" - Page 8
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Showing 212 open source projects for "gpu processing"
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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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GENIE (GEne-geNe IntEraction)
GPU based Parallel Gene-Gene Interaction Analysis
...Here we present a novel software package GENIE, which utilizes the power of multiple GPU or CPU processor cores to parallelize the interaction analysis. Citation: Chikkagoudar, S., Wang, K., & Li, M. (2011). GENIE: a software package for gene-gene interaction analysis in genetic association studies using multiple GPU or CPU cores. BMC research notes, 4(1), 158. -
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gpgmpi
An GPGMP in C++/OpenCL with improved time step algorithm
The need for speed is always a challenge for large-scale stochastic simulation. This software is based on a parallel stochastic simulation algorithm already implemented on Graphics Processing Unit (GPU) for inhomogeneous reaction-drift-diffusion systems. We suggest an improved choice of time step which turns out to be almost 3 or even more times fast with nearly identical accuracy. The software is now completely implemented in C++ and OpenCL which only depends on boost library and GPU vendor’s OpenCL SDK. It can be easily set up with Microsoft Visual Studio on Windows platform. ... -
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FASTCUDA
Execution of CUDA programs on a Heterogeneous FPGA-based Architecture
FASTCUDA methodology proposes the use of CUDA, a Graphical Processing Unit (GPU) language which exposes parallelism at source code in a FPGA hardware acceleration environment.The FASTCUDA toolset splits, with minimal user intervention, application's code into two parts: one that will be compiled and executed as parallel software in an embedded Multi-core, and another that will be synthesized and implemented with multiple special-purpose accelerators in hardware. -
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A scheme to significantly speed up the processing of MRI with FreeSurfer (FS) is presented. The scheme is aimed at maximizing the productivity (number of subjects processed per unit time) for the use case of research projects with datasets involving many acquisitions. The scheme combines the already existing GPU-accelerated version of the FS workflow with a task-level parallel scheme supervised by a resource scheduler.
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Java/C Comparative Benchmarks
Java and C Comparative Performance Benchmarks
...Some of the benchmarks are also implemented in Python and Scala. There are benchmarks for bit twiddling, numerical computing, data structure manipulation, concurrent computing, callouts to native libraries, and, graphics processing units (GPU) utilization. -
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DistributedCL is a middleware that provides location-transparent GPU processing to applications developed using the OpenCL API. Moved to GitHub. https://github.com/andrelrt/distributedcl
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OpenShader
Open architecture GPU simulator and implementation
Documentation, simulator, compiler, and Verilog implementation of a completely open-architecture graphics processing unit. This design is intended for academic and commercial purposes. The first step is to develop a detailed GPU simulator and compiler. The second step is to implement the GPU in synthesizable Verilog. The third step is to develop a feedback loop between the simulator and implementation, allowing power, performance, and reliability aspects of the hardware to feed back into ever more detailed and accurate simulations of a complete GPU. ... -
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LBP in multiple platforms
LBP implementation in multiple computing platforms (ARM,GPU, DSP...)
...When selecting a suitable LBP implementation platform, the specific application and its requirements in terms of performance, size, energy efficiency, cost and developing time has to be carefully considered. This is a software toolbox that collects software implementations of the Local Binary Pattern operator in several platforms: - 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 -
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Swift Sequence Alignment Program
GPU-based DNA sequence alignment program using Smith-Waterman
Swift is a DNA sequence alignment program that produces gapped alignment using the Smith-Waterman algorithm. It takes in a query file (FASTA format) and a reference file (FASTA format) as input. It outputs the reference name, read name, gapped alignment, alignment score, alignment start and end positions, and alignment length. I gave a talk on Swift in the GPU Technology Conference 2012. The talk can be accessed at... -
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Pixma Frontpanel Library
Library for using Canon Pixma inkjet printer frontpanels
This library makes it possible to reuse the LCD/button frontpanels of Canon Pixma MP620 / MP630 inkjet printers in your own projects. The library makes use of the processing power and RAM that is built into the frontpanels. The library is written for maple / olimexino but might be expanded in the future. Please see the wiki for info on how the display works, the protocol used and how to connect your display to your board: http://sourceforge.net/p/pixmafrontpanel/wiki/Home/ -
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Feynman Path Integrals with GPU
GPU Implementation of the Feynman Path-Integral Method in Quantum Mec.
...Using Monte Carlo techniques with the Metropolis algorithm, ground state energies are calculated for the physical systems. All this is implemented in a neat little program to be run on a Graphical Processing Unit through Python and OpenCL (with PyOpenCL). -
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Parallelization of Complex Event Processing on GPGPU
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GPU-accelerated LIBSVM is a modification of the original LIBSVM that exploits the CUDA framework to significantly reduce processing time while producing identical results. The functionality and interface of LIBSVM remains the same.
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GPUBench2 is a cross platform suite to analyze the performance of GPU( Graphics Processing Unit). GPUBench2 will gather of state-of-the-art parameters from different interfaces ( OpenGL, Cg, CUDA) available.
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An editor to yours raw pictures, with best performances: GPU processing. It use equaly the Qt4 library for the graphic user interface.
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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...
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Qaquarelle is the opensource Qt4-based graphical editor, whose goal is to provide the native way of painting with emulated traditional instruments, including the full support of tablet input and OpenGL-based processing in GPU.
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This code is provided as supplementary material for the book chapter "Exploiting graphics processing units for computational biology and bioinformatics," by Payne, Sinnott-Armstrong, and Moore.
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A gathering of state-of-the-art tools for GPU based image processing. They are the sourcecode for related research articles, and provide the basis for own experimentation. All are being implemented forNVidia GPUs in Linux, hence the name "nvision" ;)
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gpucalc is a library for computation using Graphical Processing Unit (GPU) and Central Processing Unit (CPU).
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The GWO library is numerical calculation library for the diffraction integrals using a GPU (Graphics Processing Unit). If optics engineers and researchers have no knowledge of GPU, the GWO library provides them with the GPU calculation power easily.
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BrokenFinger is a collection of demo 3D programs showing latest implementation in the areas of: Document Object Model, GPU Bound Processing, and Procedural Modeling(e.g. CGA Shape).
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proGPUKLT is a library for the Processing programming language and environment that wraps a GPU-implementation of the Kanade-Lucas-Tomasi feature tracker used for computer vision applications.
