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CPU-GPU collaboration boost performance by 20%

Posted: 09 Feb 2012     Print Version  Bookmark and Share

Keywords:GPU  CPU  processor  research 

A new technique allows graphics processing units (GPUs) and central processing units (CPUs), placed on a single chip, to collaborate. This collaboration can boost processor performance by an average of more than 20 per cent, claimed researchers from North Carolina State University.

"Our approach is to allow the GPU cores to execute computational functions, and have CPU cores pre-fetch the data the GPUs will need from off-chip main memory," Dr. Huiyang Zhou, an associate professor of electrical and computer engineering who co-authored a paper on the research. The paper presents a new approach to utilise the CPU resource to facilitate the execution of GPGPU programmes on fused CPU-GPU architectures.

"This is more efficient because it allows CPUs and GPUs to do what they are good at. GPUs are good at performing computations. CPUs are good at making decisions and flexible data retrieval."

This approach has not been possible in the past, because CPUs and GPUs were located on separate chips.

In preliminary testing, Zhou's team found that its new approach improved fused processor performance by an average of 21.4 per cent. The research can be applied to both AMD Fusion and Intel's latest generation Sandy Bridge architecture.

"Chip manufacturers are now creating processors that have a 'fused architecture,' meaning that they include CPUs and GPUs on a single chip," said Zhou. "This approach decreases manufacturing costs and makes computers more energy efficient. However, the CPU cores and GPU cores still work almost exclusively on separate functions. They rarely collaborate to execute any given programme, so they aren't as efficient as they could be. That's the issue we're trying to resolve."

The research paper is due to be presented at the 18th International Symposium on High Performance Computer Architecture, in New Orleans, on Feb 27.

Interestingly, the research was part-funded by AMD; while Mike Mantor from AMD has been named as co-author of this paper.





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