Search Results for "cuda"

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.

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.

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: You need to download a SVN client and then from command line: svn export http://svn.code.sf.net/p/gpumat/code/trunk ....

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++.

Blit contains a group of highly efficient iterative sparse solvers that can handle multiple right-hand-sides (i.e. block solvers). We will implement BLQMR, BLGMRES and other block algorithms in MATLAB, FORTRAN 90, C/C++, CUDA and OpenCL.