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MACHINE LEARNING CLASSIFICATION ON HARDWARE ACCELERATORS WITH STACKED MEMORY

  • US 20160379137A1
  • Filed: 06/29/2015
  • Published: 12/29/2016
  • Est. Priority Date: 06/29/2015
  • Status: Active Grant
First Claim
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1. A method for processing on an acceleration component a machine learning classification model comprising a plurality of decision trees, the decision trees comprising a first amount of decision tree data, the acceleration component comprising an acceleration component die and a memory stack disposed in an integrated circuit package, the memory die comprising an acceleration component memory having a second amount of memory less than the first amount of decision tree data, the memory stack comprising a memory bandwidth greater than about 50 GB/sec and a power efficiency of greater than about 20 MB/sec/mW, the method comprising:

  • slicing the model into a plurality of model slices, each of the model slices having a third amount of decision tree data less than or equal to the second amount of memory;

    storing the plurality of model slices on the memory stack; and

    for each of the model slices;

    copying the model slice to the acceleration component memory; and

    processing the model slice using a set of input data on the acceleration component to produce a slice result.

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