公开(公告)号：US20230325462A1

公开(公告)日：2023-10-12

申请号：US18296165

申请日：2023-04-05

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Gopinath Vasanth MAHALE ,  Pramod Parameshwara UDUPA ,  Jun-Woo JANG ,  Kiran Kolar CHANDRASEKHARAN ,  Sehwan LEE

IPC: G06F17/14 ,  G06N3/0464 ,  G06F7/544

CPC classification number: G06F17/14 ,  G06N3/0464 ,  G06F7/5443

Abstract: A processor-implemented apparatus includes a forward transform module configured to transform input feature maps (IFMs) by performing a forward transform operation in a Winograd convolution (WinConv) domain, multiply and accumulate array (MAA) units configured to multiply the transformed IFMs by transformed kernels and perform a first inverse transform operation based on results of the multiplying, and an inverse transform module configured to generate output feature maps (OFMs) based on a result of the first inverse transform operation.

公开(公告)号：US20230186050A1

公开(公告)日：2023-06-15

申请号：US18107210

申请日：2023-02-08

Applicant: Samsung Electronics Co., Ltd.

Inventor： Saptarsi DAS ,  Sabitha KUSUMA ,  Sehwan LEE ,  Ankur DESHWAL ,  Kiran Kolar CHANDRASEKHARAN

IPC: G06N3/04 ,  G06F17/16

CPC classification number: G06N3/04 ,  G06F17/16

Abstract: A method and an apparatus for processing layers in a neural network fetch Input Feature Map (IFM) tiles of an IFM tensor and kernel tiles of a kernel tensor, perform a convolutional operation on the IFM tiles and the kernel tiles by exploiting IFM sparsity and kernel sparsity, and generate a plurality of OFM tiles corresponding to the IFM tiles.

公开(公告)号：US20210027151A1

公开(公告)日：2021-01-28

申请号：US16935500

申请日：2020-07-22

Applicant: Samsung Electronics Co., Ltd.

Inventor： Pramod Parameshwara UDUPA ,  Kiran Kolar CHANDRASEKHARAN ,  Sehwan LEE

IPC: G06N3/063 ,  G06N3/08 ,  G06N3/04

Abstract: A processor-implemented method for generating Output Feature Map (OFM) channels using a Convolutional Neural Network (CNN), include a plurality of kernels, includes generating at least one encoded Similar or Identical Inter-Kernel Weight (S/I-IKW) stream, converting, similar and identical weights in the at least one non-pivot kernel to zero to introduce sparsity into the at least one non-pivot kernel, broadcasting at least one value to the at least one non-pivot kernel, and generating at least one OFM channel by accumulating an at least one previous OFM value with any one or any combination of any two or more of a convolution of non-zero weights of the pivot kernel and pixels of the Input Feature Map (IFM), the at least one broadcasted value, and a convolution of non-zero weights of the at least one non-pivot kernel and pixels of the IFM.

公开(公告)号：US20210263738A1

公开(公告)日：2021-08-26

申请号：US17186161

申请日：2021-02-26

Applicant: Samsung Electronics Co., Ltd.

Inventor： Arnab ROY ,  Kiran Kolar CHANDRASEKHARAN ,  Sehwan LEE

IPC: G06F9/30

Abstract: A method for performing a pooling operation in bitwise manner, the method includes performing a pooling operation on ternary data upon receiving an input ternary vector, receiving an input binary vector, providing a fused hardware for performing the pooling operation on any of the received binary and the ternary data, and executing the pooling operation performed bitwise through the fused hardware.

公开(公告)号：US20200293858A1

公开(公告)日：2020-09-17

申请号：US16816861

申请日：2020-03-12

Applicant: Samsung Electronics Co., Ltd.

Inventor： Saptarsi DAS ,  Sabitha KUSUMA ,  Sehwan LEE ,  Ankur DESHWAL ,  Kiran Kolar CHANDRASEKHARAN

IPC: G06N3/04 ,  G06F17/16

Abstract: A method and an apparatus for processing layers in a neural network fetch Input Feature Map (IFM) tiles of an IFM tensor and kernel tiles of a kernel tensor, perform a convolutional operation on the IFM tiles and the kernel tiles by exploiting IFM sparsity and kernel sparsity, and generate a plurality of OFM tiles corresponding to the IFM tiles.