公开(公告)号：US20170257287A1

公开(公告)日：2017-09-07

申请号：US15219549

申请日：2016-07-26

Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

Inventor： Young-Joo KIM ,  Yung Joon JUNG ,  Jeong-Si KIM

IPC: H04L12/24 ,  H04L12/26

CPC classification number: H04L41/5038 ,  H04L43/0817 ,  H04L43/10

Abstract: Provided herein is a real-time QoS monitoring apparatus, including an application registration unit configured to register at least one monitoring target application program for QoS measurement; a function explorer unit configured to detect user-defined functions in application code of the at least one monitoring target application program; a loop-statement explorer unit configured to detect loop-statements in the application code; a user-defined location explorer unit configured to detect user-defined locations in the application code; and a heartbeat generator configured to generate a plurality of heartbeat calls to correspond to the functions detected by the function finder, the loop-statements detected by the loop finder, and the user-defined locations detected by the user-defined location finder. Accordingly, there are provided a real-time QoS monitoring apparatus and method, which may measure QoS in real time without additionally modifying the application program.

公开(公告)号：US20240176664A1

公开(公告)日：2024-05-30

申请号：US18347352

申请日：2023-07-05

Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

Inventor： Young-Joo KIM

IPC: G06F9/50

CPC classification number: G06F9/5027

Abstract: Disclosed herein are an artificial intelligence application provision method and apparatus for supporting Edge computing for Cyber-Physical Systems (EdgeCPS). The artificial intelligence application provision method includes receiving an artificial intelligence application and service specification, obtaining artificial intelligence-related information allocated from an artificial intelligence information sharing database based on the artificial intelligence application and service specification, creating a pipeline specification corresponding to the artificial intelligence application and service specification, and allocating resources corresponding to respective pipelines using the pipeline specification.

公开(公告)号：US20210357749A1

公开(公告)日：2021-11-18

申请号：US17104932

申请日：2020-11-25

Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

Inventor： Young-Joo KIM

IPC: G06N3/08 ,  G06N3/04

Abstract: The disclosed embodiment relates generally to technology for training AI for recognizing objects, and more particularly to a method for partial training of AI. The method includes generating preprocessed input data by preprocessing input data, generating an inference result by inputting the preprocessed input data to the existing learning model of an inferrer, determining whether partial training is required based on the inference result, generating a partial-training dataset by combining first data, corresponding to the existing learning model, with second data, corresponding to the preprocessed input data, when it is determined that partial training is required, and performing partial training by inputting the partial-training dataset to a learner.

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：US20160274636A1

公开(公告)日：2016-09-22

申请号：US14865537

申请日：2015-09-25

Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

Inventor： Young-Joo KIM

IPC: G06F1/28

CPC classification number: G06F1/28 ,  G06F1/26 ,  G06F1/329 ,  G06F9/50 ,  G06F11/2273 ,  Y02D10/24

Abstract: Provided is a method for measuring power of a graphics processing unit. The method includes changing a utilization of the graphics processing unit through an application programming interface (API), measuring and storing the utilization or a driving frequency of the graphics processing unit for each trace time, measuring and storing power consumption of the graphics processing unit for each trace time, and synchronizing the utilization of the graphics processing unit with the power consumption according to a stored trace time and calculating a power coefficient for each driving frequency with reference to synchronized information.

Abstract translation: 提供了一种用于测量图形处理单元的功率的方法。 该方法包括通过应用编程接口（API）来改变图形处理单元的利用率，测量和存储每个跟踪时间的图形处理单元的利用率或驱动频率，测量和存储图形处理单元的功耗，以便 每个跟踪时间，并且根据存储的跟踪时间来同步图形处理单元的利用率与功耗，并且参考同步信息来计算每个驱动频率的功率系数。