We are pleased to annouce the release of a new OpenCL.NET library supporting OpenCL™ 1.1 (revision 44) driver API by the Khronos group.
This release includes all API functions described by the standard and targets cross-platform HPC and GPGPU applications.
OpenCL.NET can be used to develop solutions under Windows, Linux or Mac, also integrating with Matlab to accelerate algorithms of different kinds.
All vendors are supported, including NVIDIA®, Intel® and AMD.
We are happy to announce the release of CUDA.NET version 3.0.0.
This release provides support for latest CUDA 3.0 API and few more updates that will make programming with CUDA from .NET easier and faster.
Support for CUDA 3.0 API
Added memset functions for CUDA class
Supporting new graphics interoperability functions
Improved generics support for memory operations
Added CUDAContextSynchronizer class
Improved memory operations
We employ GCHandle class to be used with generic memory copies in CUDA class. This method allows to work with every data type (existing vectors or user defined) natively in .NET. The implication is that now you can copy existing custom arrays of structures/classes (user data-types) to device with memory copy functions.
This class was added to assist developers in multi-GPU and multi-threaded environments sharing the same device. It uses existing CUDA API to manipulate the context each thread is attached to and provides .NET means to synchronize between threads sharing the same device for different computations.
Find it under the Tools namespace, the documentation includes a description of how to use it.
We hope you will enjoy this release.
As always, please send us comments or suggestions to: email@example.com.
We are glad to introduce a new library for video decoding, Vicodeo™, featuring accelerated performance for faster than real-time decoding of H.264, MPEG-2 (and more) video streams – in managed environments (.NET / Java).
Video processing nowadays has become a computing intensive task. Being able to accelerate decoding and various processing tasks, opens the door for many types of applications and usage of video in life, from: high-quality films, security/surveillance cameras, live events, video conversations over the web and much more.
Our library provides many capabilities beyond real-time (+) decoding of 1080p (Full HD) streams:
Codec support: H.264, MPEG-2, VC-1 and more
Color space conversion from YUV 4:2:0 to RGB (accelerated)
Integrated parser for elementary/transport streams and video packets
Simple integration with DirectX or OpenGL
Faster than real-time decoding for 1080p even on low-end platforms
Optional immediate decoding of frames, without buffering
We are happy to announce the immediate availability of OpenCL.NET for the public.
This library provides a .NET implementation and wrapping of the OpenCL interface for GPU computing (and general computing as well).
Currently, the library supports revision 1.0.43 of Khronos (being the latest version of the standard).
Users may test the library with NVIDIA released drivers for OpenCL, or on other architectures as OpenCL should be supported on (Intel, AMD CPU etc.).
The API in this release was adapted to be cross platform in mind, and code, using the new SizeT construct for transparent handling of 32/64 bit platforms.
In addition, there is only one version of the library conforming to all operating systems who support OpenCL, regardless of Windows, Linux or Mac.
The new API by NVIDIA allows to integrate existing DirectX 10 applications with CUDA, to provide another level of computing, if for post-processing, image processing or other computations to perform.
DirectX 9 API is still supported.
A new compiler support is provided by NVIDIA, through the API. This allows to generate CUDA kernel code in runtime and compile it on demand using this new facility.
In addition, it allows to attach kernel source code to an application, and compile it at the site, using specific configuration: maximum register usage, specific hardware support and more.
This release of CUDA.NET 2.1, fixes an issue with CUDAExecution class. When running a computation on the GPU using the class, an then calling the Clear method, didn’t clear the parameters state. As with this release the issue was fixed.