Displaying 1 to 15 from 15 results

vexcl - VexCL is a C++ vector expression template library for OpenCL/CUDA


VexCL is a vector expression template library for OpenCL/CUDA. It has been created for ease of GPGPU development with C++. VexCL strives to reduce amount of boilerplate code needed to develop GPGPU applications. The library provides convenient and intuitive notation for vector arithmetic, reduction, sparse matrix-vector products, etc. Multi-device and even multi-platform computations are supported. The source code of the library is distributed under very permissive MIT license.

CuBLAS.Net


A wrapper for NVidia's CuBLAS (Compute Unified Basic Linear Algebra Subprograms) for the CLR.

Npack


An implementation of linear algebra numerical structures and methods for the CLR. NPack is unique in that it uses generics for matrix element definitions, and a set of matrix operations via an interface, allowing a CLR-based operations engine as well as the opportunity to use ...




C++ AMP LAPACK Library


Project Description C++ AMP LAPACK Library is a library of linear algebra subroutines that C++ AMP developers can freely use in their own projects. Note that this project builds upon and is dependent upon the C++ AMP BLAS library. Prerequisite Understanding C++ AMP is an ...

C++ AMP: Accelerated Massive Parallelism with Microsoft Visual C++


Samples for the latest Microsoft Press book on programming with C++AMP using Visual Studio 2012.

4-Centauri


GPGPUs offer significant horsepower in our computers that are unfortunately not easily available to .NET programs. <project name> is a system capable to map .NET bytecode into GPU IL (e.g. nVidia PTX) so that you can run .NET algorithms on state of the art hardware.

GPCompute


GPCompute is an old CUDA-like but Based on DX81 (or later) for compatibility with almost any current Videocards. It's Developped in C/C++. With Simple Interface for Arrayed-Computations. The Limitation all came from its DX version implemention.



managedCUDA


managedCUDA makes the CUDA Driver API available in .net applications written in C#, Visual Basic or any other .net language. It also includes classes for an easy handling and interop with CUDA, i.e. build-in CUDA types like float3.

Optix.NET


Optix.NET is a .NET wrapper for the Nvidia Optix GPU ray-tracing library.

C++ AMP RNG Library


C++ AMP RNG Library is a library of Random Number Generators that C++ AMP developers can freely use in their own projects.

CellularSolver


The main idea of a this project - create cellular automation (CA) simulation system. We try to reduce ODE/PDE/Integral Equations models to CA-model

NyuziToolchain - Port of LLVM/Clang C compiler to Nyuzi parallel processor architecture


This is a toolchain for a parallel processor architecture called Nyuzi, based on LLVM. It includes a C/C++ compiler (clang), assembler, linker and debugger (lldb). While this project includes a C/C++ compiler, the LLVM backend can support any language. There is a small, experimental SPMD parallel compiler in tools/spmd_compiler.

dw-webgl-sketchbook - Webgl Experiments


Showroom for my Webgl Experiments. The demos require a browser that supports webgl2.

amgcl - C++ library for solving large sparse linear systems with algebraic multigrid method


AMGCL is a header-only C++ library for solving large sparse linear systems with algebraic multigrid (AMG) method. AMG is one of the most effective iterative methods for solution of equation systems arising, for example, from discretizing PDEs on unstructured grids. The method can be used as a black-box solver for various computational problems, since it does not require any information about the underlying geometry. AMG is often used not as a standalone solver but as a preconditioner within an iterative solver (e.g. Conjugate Gradients, BiCGStab, or GMRES). AMGCL builds the AMG hierarchy on a CPU and then transfers it to one of the provided backends. This allows for transparent acceleration of the solution phase with help of OpenCL, CUDA, or OpenMP technologies. Users may provide their own backends which enables tight integration between AMGCL and the user code.