US 12,118,454 B2
Neural network accelerator using logarithmic-based arithmetic
William James Dally, Incline Village, CA (US); Rangharajan Venkatesan, San Jose, CA (US); and Brucek Kurdo Khailany, Austin, TX (US)
Assigned to NVIDIA Corporation, Santa Clara, CA (US)
Filed by NVIDIA Corporation, Santa Clara, CA (US)
Filed on Dec. 12, 2023, as Appl. No. 18/537,570.
Application 18/537,570 is a continuation of application No. 16/549,683, filed on Aug. 23, 2019, granted, now 11,886,980.
Prior Publication US 2024/0112007 A1, Apr. 4, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G06N 3/063 (2023.01); G06F 7/483 (2006.01); G06F 17/16 (2006.01)
CPC G06N 3/063 (2013.01) [G06F 7/4833 (2013.01); G06F 17/16 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method, comprising:
receiving a plurality of input values comprising image or sound data at a tensor core within a processor, wherein
each input value in the plurality of input values is represented in a logarithmic format including a sign, a quotient component, and a remainder component,
the tensor core is configured to implement at least one layer of a neural network model, and
the at least one layer processes the plurality of input values by:
generating a set of partial sums by sorting the quotient component for each input value according to the remainder component for the input value;
summing the partial sums in the set of partial sums to produce a result that is a sum of the plurality of input values;
using the result within at least one of an autonomous vehicle platform, financial modeling system, robotics system, speech recognition system, text recognition system, image recognition system, weather forecasting system, video analytics system, molecular simulation system, disease diagnosis system, data analytics system, molecular dynamics simulation system, factory automation system, real-time language translation system, online search optimization system, or personalized user recommendations system.