Convolutional neural network acceleration system based on unstructured sparseness
A convolutional neural network and unstructured technology, applied in the field of accelerators, can solve the problems that accelerators cannot be effective and accelerated, and achieve the effects of reducing delay, flexible calculation process, and improving calculation efficiency
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[0052]The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of this application.
[0053] The unstructured sparseness for DCNN has high hopes for hardware acceleration due to its large-scale compression of computational complexity. However, due to the high irregularity of the distribution of parameters after the unstructured sparse process, different problems will be introduced when implemented on general-purpose acceleration platforms (CPU, GPU) and dedicated acceleration platforms for dense neural networks: 1) processing unit ( processin...
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