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System and method for accelerating and optimizing the processing of machine learning techniques using a graphics processing unit

机译:使用图形处理单元加速和优化机器学习技术处理的系统和方法

摘要

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.
机译:一种用于使用图形处理单元(GPU)处理机器学习技术(例如神经网络)和其他非图形应用程序的系统和方法,以加速和优化处理。该系统和方法将可用于多种机器学习技术的架构从CPU转移到GPU。使用几种新颖的技术可以将处理转移到GPU,这些技术可以克服这些限制,并且可以在GPU体系结构的框架内很好地工作。克服了这些限制后,机器学习技术特别适合在GPU上进行处理,因为GPU通常比典型的CPU功能强大得多。而且,类似于图形处理,机器学习技术的处理涉及解决非平凡解决方案和大量数据的问题。

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