公开(公告)号：US20200302291A1

公开(公告)日：2020-09-24

申请号：US16729135

申请日：2019-12-27

Applicant: Electronics and Telecommunications Research Institute

Inventor： Seung-Tae HONG

IPC: G06N3/08 ,  G06F9/38 ,  G06F9/50 ,  G06F9/54 ,  G06F17/16

Abstract: Disclosed herein are a convolutional layer acceleration unit, an embedded system having the convolutional layer acceleration unit, and a method for operating the embedded system. The method for operating an embedded system, the embedded system performing an accelerated processing capability programmed using a Lightweight Intelligent Software Framework (LISF), includes initializing and configuring, by a parallelization managing function entity (FE), entities present in resources for performing mathematical operations in parallel, and processing in parallel, by an acceleration managing FE, the mathematical operations using the configured entities.

公开(公告)号：US20190228344A1

公开(公告)日：2019-07-25

申请号：US16013847

申请日：2018-06-20

Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

Inventor： Seung-Tae HONG ,  Young-Joo KIM ,  Jeong-Si KIM ,  Jin-Ho SEOL

IPC: G06N99/00 ,  G06F17/11

Abstract: Disclosed herein are an apparatus and method for adaptively accelerating a BLAS operation based on a GPU. The apparatus for adaptively accelerating a BLAS operation based on a GPU includes a BLAS operation acceleration unit for setting optimal OpenCL parameters using machine-learning data attribute information and OpenCL device information and for creating a kernel in a binary format by compiling kernel source code; an OpenCL execution unit for creating an OpenCL buffer for a BLAS operation using information about an OpenCL execution environment and the optimal OpenCL parameters and for accelerating machine learning in an embedded system in such a way that a GPU that is capable of accessing the created OpenCL buffer performs the BLAS operation using the kernel, and an accelerator application unit for returning the result of the BLAS operation to a machine-learning algorithm.

公开(公告)号：US20220300803A1

公开(公告)日：2022-09-22

申请号：US17342354

申请日：2021-06-08

Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

Inventor： Hyun-Woo CHO ,  Jeong-Si KIM ,  Hong-Soog KIM ,  Jin-Wuk SEOK ,  Seung-Tae HONG

IPC: G06N3/08 ,  G06N3/04

Abstract: Disclosed herein are a method for performing a dilated convolution operation using an atypical kernel pattern and a dilated convolutional neural network system using the same. The method for performing a dilated convolution operation includes learning a weight matrix for a kernel of dilated convolution through deep learning, generating an atypical kernel pattern based on the learned weight matrix, and performing a dilated convolution operation on input data by applying the atypical kernel pattern to a kernel of a dilated convolutional neural network.