公开(公告)号：US20210240925A1

公开(公告)日：2021-08-05

申请号：US17102679

申请日：2020-11-24

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Sejung KWON ,  Dongsoo Lee

IPC: G06F40/205 ,  G06F40/237 ,  G06F12/0813 ,  G06N3/04

Abstract: An electronic device is provided. The electronic device includes a first memory configured to operate at a first speed and store compressed vectors corresponding to words, and scaling factors corresponding to the compressed vectors; a second memory that is faster than the first memory and is configured to store a first group of the compressed vectors, and store a first group of the scaling factors; and a processor configured to obtain a first compressed vector and a first scaling factor corresponding to an input word from the first memory or the second memory and process the obtained first compressed vector and the obtained first scaling factor by using a neural network.

公开(公告)号：US20200234131A1

公开(公告)日：2020-07-23

申请号：US16727323

申请日：2019-12-26

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Dongsoo LEE ,  Sejung KWON ,  Parichay KAPOOR ,  Byeoungwook KIM

IPC: G06N3/08 ,  G06N3/04 ,  G06F17/16

Abstract: An electronic apparatus is provided. The electronic apparatus includes sample data and memory storing a first matrix included in an artificial intelligence model trained based on sample data, and a processor configured to prunes each of a plurality of first elements included in the first matrix based on a first threshold, and acquire a first pruning index matrix that indicates whether each of the plurality of first elements has been pruned with binary data, factorize the first matrix to a second matrix of which size was determined based on the number of rows and the rank, and a third matrix of which size was determined based on the rank and the number of columns of the first matrix, prunes each of a plurality of second elements included in the second matrix based on a second threshold, and acquire a second pruning index matrix that indicates whether each of the plurality of second elements has been pruned with binary data, prunes each of a plurality of third elements included in the third matrix based on a third threshold, and acquire a third pruning index matrix that indicates whether each of the plurality of third elements has been pruned with binary data, acquire a final index matrix based on the second pruning index matrix and the third pruning index matrix, and update at least one of the second pruning index matrix or the third pruning index matrix by comparing the final index matrix with the first pruning index matrix.