- 专利标题: PARALLEL COMPUTATIONAL ARCHITECTURE WITH RECONFIGURABLE CORE-LEVEL AND VECTOR-LEVEL PARALLELISM
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申请号: US16008949申请日: 2018-06-14
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公开(公告)号: US20190385046A1公开(公告)日: 2019-12-19
- 发明人: Andrew S. Cassidy , Myron D. Flickner , Pallab Datta , Hartmut Penner , Rathinakumar Appuswamy , Jun Sawada , John V. Arthur , Dharmendra S. Modha , Steven K. Esser , Brian Taba , Jennifer Klamo
- 申请人: INTERNATIONAL BUSINESS MACHINES CORPORATION
- 主分类号: G06N3/063
- IPC分类号: G06N3/063 ; G06F15/80 ; G06N3/04
摘要:
Neural network processing hardware using parallel computational architectures with reconfigurable core-level and vector-level parallelism is provided. In various embodiments, a neural network model memory is adapted to store a neural network model comprising a plurality of layers. Each layer has at least one dimension and comprises a plurality of synaptic weights. A plurality of neural cores is provided. Each neural core includes a computation unit and an activation memory. The computation unit is adapted to apply a plurality of synaptic weights to a plurality of input activations to produce a plurality of output activations. The computation unit has a plurality of vector units. The activation memory is adapted to store the input activations and the output activations. The system is adapted to partition the plurality of cores into a plurality of partitions based on dimensions of the layer and the vector units.
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