REDUCING POWER CONSUMPTION IN A NEURAL NETWORK PROCESSOR BY SKIPPING PROCESSING OPERATIONS

REDUCING POWER CONSUMPTION IN A NEURAL NETWORK PROCESSOR BY SKIPPING PROCESSING OPERATIONS

A deep neural network ("DNN") module compresses and decompresses neuron-generated activation data to reduce the utilization of memory bus bandwidth. The compression unit receives an uncompressed chunk of data generated by a neuron in the DNN module. The compression unit generates a mask po...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: AMBARDEKAR, Amol Ashok, CEDOLA, Kent D, MCBRIDE, Chad Balling, BOBROV, Boris, PETRE, George, WALL, Larry Marvin
Format: Patent
Sprache:eng ; fre ; ger
Schlagworte:
CALCULATING
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
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Beschreibung
Zusammenfassung:A deep neural network ("DNN") module compresses and decompresses neuron-generated activation data to reduce the utilization of memory bus bandwidth. The compression unit receives 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 receives 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.