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 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.
A special event is about to take place between 18-23 July, 2010 in Barcelona, Spain.
The session on Computational Intelligence on Consumer Games and Graphics Hardware (CIGPU 2010) will be part of IEEE World Congress on Computational Intelligence Conference 2010 (WCCI-2010).
Building on the success of previous CIGPU sessions and workshops, CIGPU 2010 will further explore the role that GPU technologies can play in computational intelligence (CI) research. Submissions of original research are invited on the use of parallel graphics hardware for computational intelligence. Work might involve exploring new techniques for exploiting the hardware, new algorithms to implement on the hardware, new applications for accelerated CI, new ways of making the technology available to CI researchers or the utilisation of the next generation of technologies.
“Anyone who has implemented computational intelligence techniques using any parallel graphics hardware will want to submit to this special session.”
Thanks to Dr. Simon Harding, Memorial University, Canada, for sharing this information with us.
In addition, the session will discuss using CUDA.NET for running related simulations on the GPU.
We would like to announce for the release of CUDA.NET 2.3.7.
This version addresses various issues with runtime API and types. The change was in data types and structures compliance with the native wrapper of CUDA Runtime API, to support cross-platform environments operating in 32 or 64 bit mode. The structures now support the SizeT structure we introduced in the previous CUDA.NET release.
We added support for Amazon S3 storage services recently to Hoopoe. Following the previous article with our general account details, we wanted to share with you a regular expression we use for validating S3 URL as sources of data and files.
You may find more information about S3 naming conventions and requirements in the manuals available from http://aws.amazon.com/s3.
When submitting a task to Hoopoe with input/output sources from Amazon S3, one must specify the S3 URL of the resource. A simple format for a resource can be: https://test-bucket.s3.amazonaws.com/dir1/input.bin.
With this example, the bucket of the user storing the object is called “test-bucket“, and the file for input is “dir1/input.bin”, called the key of the object (in the bucket).
This is a general form for S3 URL to make them accessible over the internet.
We are using a regular expression to validate all Amazon S3 URLs with submitted tasks to Hoopoe.
In .NET (and general) manners, the RegEx is: https://[a-z0-9][a-z0-9-.]*.s3.amazonaws.com/[w][wW]*
As you may see, the following limitations exist:
For DNS compatibility, bucket names must be lower case and start with a letter or number
In S3, and following DNS limitations, bucket names should not exceed 63 characters in length
Object keys can be of variable length, must start with a valid character but can follow with other possible characters, also to denote paths (a file named: “dir/input.bin” is located under “dir” directory)
In addition to the above, Hoopoe restricts S3 URL to be up to 256 characters in length
In case you find a mistake in the regular expression definition, whether possible URLs do not fit or it is permissive, please send us an email.
We also hope you may find this information useful for your own purposes.
We are pleased to announce that recently we added Amazon S3 services support, integrated to Hoopoe.
Using Amazon S3 services users can have extended storage support from Amazon Web Services (AWS), also communicating with other cloud systems, such as EC2 and more, to offer variety of processing capabilities.
Users who would like to use Amazon S3 can do it with a very intuitive interface, specifying the buckets and objects they use, following S3 semantics and terms, so Hoopoe can offer bi-directional communication with S3, for reading data, and outputting computed results.
We will follow with more articles presenting best practices guide for using Amazon S3 with Hoopoe.
As general information, users can use the following details to recognize Hoopoe in Amazon S3.