New examples are available on the CLFORTRAN page.
- Quering platforms and devices information
- Creating OpenCL context and command queue
- Basic device IO with Fortran arrays and validity testing
In addition, CLFORTRAN API was improved for better OpenCL functionality support in Fortran.
We are pleased to announce CLFORTRAN for GPGPU.
CLFORTRAN is a new and elegant Fortran module that allows integration of OpenCL with Fortran programs easier than ever.
Taking advantage of Fortran language features, it is written in pure Fortran – aka no C/C++ code is required to utilize the GPGPU.
CLFORTRAN is compatible with all major compilers: GNU, Intel and IBM, and supporting OpenCL 1.2 API.
In addition, it is provided as open source and licensed under LGPL, to allow scientific computing at massive scales and all supported vendors.
You may read more at CLFORTRAN.
Intel® have just introduced their Xeon® Phi™ processor to the market, targeting HPC and scientific computing. It is available for purchase and integration into existing systems/platforms/servers.
The new co-processor is a discrete device that runs an operating system of its own and functions as a fully functional computer (though being a co-processor).
Why should anyone be interested in Xeon® Phi™?
It is based on the most common x86 architecture, therefore porting existing code and algorithms should be the easiest possible.
One may also utilize OpenCL™ algorithms to take advantage of the high-parallelism of the Phi™ processor.
In addition, it features 60 cores, 8GB of internal memory (with 320 GB/s) and uses PCIe x16 slot to provide high performance bandwidth throughput.
With almost 1 TFLOPS of double precision, Phi™ is competent to very high end GPUs in the market today, but on some aspects, provides better performance and industrial matching than other vendors.
You can read more at:
Contact us for more details and projects regarding Intel® Xeon® Phi™ family of processors.
We are happy to announce the availability of NVIDIA® CARMA® platforms, providing an ARM based system (Tegra® 3) cooperating with an internal and a discrete GPU (NVIDIA® Quadro® 1000M utilizing 96 cores).
NVIDIA® CARMA® aims to provide an energy-effecient HPC solution, targeting low-power, small form factor environments.
Software support is provided for CUDA® 5, with FFT, BLAS, image processing, accelerated video decoding/encoding (H.264, H.265, VC-1, MPEG-2 etc.) and much more.
Both Linux, Android and Windows® 8 operating systems are supported.
Hardware platforms are available in ruggedized form factor as well for outdoor, defense or military purposes.
This opens new opportunities for embedded like GPGPU solutions, for digital signage, medical imaging and other handheld/mobile usage.
For more information: 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
- And more!
For more information: Video Decoding.
We are pleased to announce a call for contribution for case studies and customer stories using CUDA.NET to be presented in our web site.
We invite organizations, research institutes and privates to tell us about about their use of CUDA.NET for different purposes – developing a product, researching variety of scientific fields and more.
Users willing to contribute their story are invited to send their details to the following address: email@example.com and we will contact them soon.
Thank you for your cooperation.
Welcome to our new blog system.
We are intending to publish in the blogs material and resources related to programmers and other users who are interested in HPC or GPU Computing techonologies.
The blogs will be used by us on regular basis to share and discuss issues presented by users of our products, such as: CUDA.NET, OpenCL.NET, FORTRAN and more.
We hope you will find it useful!