With blogposts about the Geforce GTX 680 springing up already we thought we would take a look at the likely specification of the likely next major incarnation from GPU wizards Nvidia.

We will look at the features of previous Geforce GTX GPUs and then try and make an estimated guess on the likely specifications of the Nvidia Geforce GTX 680 we can then start to estimate the possible performance and suitability of such a beast.

Oh and we will be applying this highly dubious guesswork to the mobile version because we are a laptop review site.

Coming soon!

• NVIDIA CUDA Platform Compiler Source Code

This was announced in a press release on Dec 13th 2011, informing the public that NVIDIA has released the CUDA Platform Compiler Source Code and opens the CUDA platform. The press release is available below:-


Enables Researchers, Software Tool Developers to Add New Language and Architecture Support to Popular Parallel Programming Model

BEIJING -- (Marketwire) -- 12/13/2011 -- GTC Asia -- NVIDIA today announced that it will provide the source code for the new NVIDIA® CUDA® LLVM-based compiler to academic researchers and software-tool vendors, enabling them to more easily add GPU support for more programming languages and support CUDA applications on alternative processor architectures.

LLVM is a widely-used open source compiler infrastructure with a modular design that makes it easy to add support for new programming languages and processor architectures. It is used for a range of programming requirements by many leading companies, including Adobe, Apple, Cray, Electronic Arts, and others.
The new LLVM-based CUDA compiler, which is enhanced with architecture support for NVIDIAs parallel GPUs, is included in the latest release of the CUDA Toolkit (v4.1), now available to the public.

"Opening up the CUDA platform is a significant step," said Sudhakar Yalamanchili, professor at Georgia Institute of Technology and lead of the Ocelot project, which maps software written in CUDA C to different processor architectures. "The future of computing is heterogeneous, and the CUDA programming model provides a powerful way to maximize performance on many different types of processors, including AMD GPUs and Intel x86 CPUs."

Enabling alternative approaches to programming heterogeneous parallel systems for domain-specific problems and future programming models will help accelerate the path to exascale computing. By releasing the source code to the CUDA compiler and internal representation (IR) format, NVIDIA is enabling researchers with more flexibility to map the CUDA programming model to other architectures, and furthering development of next-generation higher performance computing platforms.

Software tools vendors can also access compiler source code technology to build custom solutions.
"This initiative enables PGI to create native CUDA Fortran and OpenACC compilers that leverage the same device-level optimization technology used by NVIDIA CUDA C/C++," said Doug Miles, director of The Portland Group. "It will enable seamless debugging and profiling using existing tools, and allow PGI to focus on higher-level optimizations and language features."

Early access to the CUDA compiler source code is available for qualified academic researchers and software tools developers by registering here: http://developer.nvidia.com/cuda-source.

To learn more about the NVIDIA CUDA programming environment, visit the CUDA web site.




Data taken from http://pressroom.nvidia.com/easyir/customrel.do?easyirid=A0D622CE9F579F09&version=live&prid=831864&releasejsp=release_157&xhtml=true