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: firstname.lastname@example.org.
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 availability of the so long waiting OpenCL.NET 1.0.48 library.
This version aligns with OpenCL 1.0.48 standard, and fully conforms with latest NVIDIA drivers for OpenCL (and as well on supported platforms).
In brief, this release of the standard added few API functions and modified some, to truly allow heterogeneous computing on a single system. An application can query for the existence of multiple computing devices on the system, also by different vendors (recognize the CPU and a GPU as compute resources) regardless of the vendor. Such that consuming different computing resources can be transparent.
For further details about standard features and changes please consult Khronos website.
The 2nd annual cloud computing summit is about to take place in Shfayim, Israel, between December 2-3, 2009.
Following last year success, the event will cover recent developments and progress in cloud technologies. Presenting with top-of-the-line companies active in this field, including (partial list): Amazon, Google, eBay, IBM, HP, Sun, RedHat and more.
Additional “hands-on” labs and workshops are offered during the event for participants that would like to learn more about cloud technologies and integration possibilities.
We are also presenting Hoopoe at the summit, for GPU Cloud Computing, and providing a workshop on GPU Computing in general and Hoopoe as well.
This event ends 2009 and symbolically the last decade, marking cloud computing as a major development that we are about to see more and more in the next years.
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.