Processing machine learning techniques using a graphics...

Details Processing machine learning techniques using a graphics... Processing machine learning techniques using a graphics...

2007-05-14

2009-06-16

Vincent, David R (Department: 2129)

Data processing: artificial intelligence

Machine learning

C382S157000

Reexamination Certificate

active

07548892

ABSTRACT:
A system and method for processing machine learning techniques (such as neural networks) and other non-graphics applications using a graphics processing unit (GPU) to accelerate and optimize the processing. The system and method transfers an architecture that can be used for a wide variety of machine learning techniques from the CPU to the GPU. The transfer of processing to the GPU is accomplished using several novel techniques that overcome the limitations and work well within the framework of the GPU architecture. With these limitations overcome, machine learning techniques are particularly well suited for processing on the GPU because the GPU is typically much more powerful than the typical CPU. Moreover, similar to graphics processing, processing of machine learning techniques involves problems with solving non-trivial solutions and large amounts of data.

REFERENCES:
patent: 5592597 (1997-01-01), Kiss
Bohn, Kohonen Feature Mapping through Graphics Hardware, 1998.
Rost, Course 17: State-of-the-Art in Shading Hardware, Chapter 6: the Opengl Shading Language, SIGGRAPH 2002 Course Notes, Aug. 5, 2002.
DACS, 250, 225 MHZ CPUS Fuel Octane, O[Sub]2 (Silicon Graphics Canada, Jun. 29, 1998.

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