- 专利标题: NEURAL NETWORK PROCESSOR USING COMPRESSION AND DECOMPRESSION OF ACTIVATION DATA TO REDUCE MEMORY BANDWIDTH UTILIZATION
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申请号: US15953356申请日: 2018-04-13
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公开(公告)号: US20180300606A1公开(公告)日: 2018-10-18
- 发明人: Joseph Leon CORKERY , Benjamin Eliot LUNDELL , Larry Marvin WALL , Chad Balling McBRIDE , Amol Ashok AMBARDEKAR , George PETRE , Kent D. CEDOLA , Boris BOBROV
- 申请人: Microsoft Technology Licensing, LLC
- 主分类号: G06N3/04
- IPC分类号: G06N3/04 ; G06N3/063 ; H03M7/30
摘要:
A deep neural network (“DNN”) module can compress and decompress neuron-generated activation data to reduce the utilization of memory bus bandwidth. The compression unit can receive an uncompressed chunk of data generated by a neuron in the DNN module. The compression unit generates a mask portion and a data portion of a compressed output chunk. The mask portion encodes the presence and location of the zero and non-zero bytes in the uncompressed chunk of data. The data portion stores truncated non-zero bytes from the uncompressed chunk of data. A decompression unit can receive a compressed chunk of data from memory in the DNN processor or memory of an application host. The decompression unit decompresses the compressed chunk of data using the mask portion and the data portion. This can reduce memory bus utilization, allow a DNN module to complete processing operations more quickly, and reduce power consumption.
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