CUDA is a parallel computing architecture from Nvidia that allows
programmers to tap Nvidia GPUs processing power for general purpose
computations. CUDA is only available for Nvidia hardware and it
programming requires specific knowledge of Nvidia GPU architectures.
On the other hand, OpenCL is a framework for writing programs that
execute across heterogeneous platforms consisting of CPUs, GPUs, and
other processors. It allows parallel code to be written and executed
across the different platforms in a computer -- usually the CPUs and
the GPU. The goal of OpenCL is to achieve code independence from the
specific architecture that will execute it, like Intel or AMD CPUs and
Nvidia or AMD/ATI GPUs. So if you write a computational code in
OpenCL, ideally, you can compile the same code for any combination of
Intel, Nvidia or AMD/ATI processors.
The Nvidia Linux drivers introduced CUDA starting from version 190.42,
but not OpenCL features.
These drivers contain, for example, the VDPAU libraries, to allow
video programs to offload portions of the video decoding process and
video post-processing to the GPU video-hardware. So if you install it
in your nvidia hybrid graphics linux laptop, you will be able to run
applications that use VDPAU for video playback. Additionally, you can
also install cuda-sdk and cuda-toolkit, and experiment with them by
writing, compiling and executing you own CUDA code.
There are already packages in the Linux system that will make use of a
CUDA-enabled system. Brandon Snider has made available commonly used
applications like mplayer or xine-lib in the Nvidia Vdpau Launchpad
Team:
http://launchpad.net/~nvidia-vdpau/+archive/ppa
This is ideal for a breed of hybrid graphics laptops like the Sony
Vaio Z-series, or the Asus UL30Vt/UL80Vt, that will seamlessly play HD
videos by enabling the computational power of the Nvidia GPU
processor.
So far, we have seen team members reporting the use of CUDA and
VDPAU-enabled applications in Linux for the Sony Vaio Z-series
laptops. Check out this blog post for more details:
http://linux-hybrid-graphics.blogspot.com/2009/12/how-to-use-nvidia-cudaopencl-linux-sdk.html
programmers to tap Nvidia GPUs processing power for general purpose
computations. CUDA is only available for Nvidia hardware and it
programming requires specific knowledge of Nvidia GPU architectures.
On the other hand, OpenCL is a framework for writing programs that
execute across heterogeneous platforms consisting of CPUs, GPUs, and
other processors. It allows parallel code to be written and executed
across the different platforms in a computer -- usually the CPUs and
the GPU. The goal of OpenCL is to achieve code independence from the
specific architecture that will execute it, like Intel or AMD CPUs and
Nvidia or AMD/ATI GPUs. So if you write a computational code in
OpenCL, ideally, you can compile the same code for any combination of
Intel, Nvidia or AMD/ATI processors.
The Nvidia Linux drivers introduced CUDA starting from version 190.42,
but not OpenCL features.
These drivers contain, for example, the VDPAU libraries, to allow
video programs to offload portions of the video decoding process and
video post-processing to the GPU video-hardware. So if you install it
in your nvidia hybrid graphics linux laptop, you will be able to run
applications that use VDPAU for video playback. Additionally, you can
also install cuda-sdk and cuda-toolkit, and experiment with them by
writing, compiling and executing you own CUDA code.
There are already packages in the Linux system that will make use of a
CUDA-enabled system. Brandon Snider has made available commonly used
applications like mplayer or xine-lib in the Nvidia Vdpau Launchpad
Team:
http://launchpad.net/~nvidia-vdpau/+archive/ppa
This is ideal for a breed of hybrid graphics laptops like the Sony
Vaio Z-series, or the Asus UL30Vt/UL80Vt, that will seamlessly play HD
videos by enabling the computational power of the Nvidia GPU
processor.
So far, we have seen team members reporting the use of CUDA and
VDPAU-enabled applications in Linux for the Sony Vaio Z-series
laptops. Check out this blog post for more details:
http://linux-hybrid-graphics.blogspot.com/2009/12/how-to-use-nvidia-cudaopencl-linux-sdk.html
Any word on when this can be used on the UL30VT?
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