June 30, 2008

Nvidia Tesla Doubles the Performance for CUDA Developers

Dresden, Germany - From video encoding to oil and gas exploration and from medical imaging to scientific research, thousands of CUDA developers in the high-performance computing (HPC) community are leveraging a GPU computing platform announced one year ago.
With more than 60,000 downloads of the C-compiler to date, the combination of CUDA and Tesla technologies have been the foundation for industry changing applications, making it the most rapidly adopted GPU computing technology platform in the HPC community.
 
This year at the International Supercomputing Conference, NVIDIA Corporation, the leader in GPU technologies, has strengthened the CUDA and Tesla technology platforms with the introduction of its second-generation platform, the new Tesla 10 series computing solutions.  Binary compatible and supporting the industry standard language of C, the new products enable developers to solve their computational challenges in a common and familiar development environment that scales effortlessly from one generation to the next with no re-coding required.  
 
The new Tesla product family includes the Tesla S1070 1U computing system and the Tesla C1060 computing processor and delivers:  
* Double the performance: up to 4 Teraflops per 1U system  
* Double precision: IEEE 754 arithmetic support  
* Double the memory: with 16 Gigabytes of memory per 1U system  
* Up to 3x the power efficiency: for a more efficient computing environment  
 
When combined with the award-winning CUDA C-language development software for parallel computing, the new Tesla products extend the reach of GPUs to any computationally intensive applications requiring double precision accuracy.
 
To date, over 70 million CUDA enabled GPUs have been sold into the market and over 60,000 downloads of the C-compiler have been recorded through the community Web site, CUDA Zone, which is located at www.nvidia.com/cuda. As a result, developers across a wide variety of fields including financial analysis, astrophysics, and seismic imaging are leveraging NVIDIA's CUDA development tools. These developers can now simply parallelize their software and exploit the GPU's parallel computing architecture to automatically distribute computing work to hundreds of processor cores.      
 
The Tesla S1070 1U computing system and Tesla C1060 computing processor board will be available for purchase for $7999 and $1699 respectively. These products are sampling and will ship in August 2008.  
 
For the free download of CUDA, visit www.nvidia.com/cuda.