• Title/Summary/Keyword: user task requirement

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Real-Time GPU Task Monitoring and Node List Management Techniques for Container Deployment in a Cluster-Based Container Environment (클러스터 기반 컨테이너 환경에서 실시간 GPU 작업 모니터링 및 컨테이너 배치를 위한 노드 리스트 관리기법)

  • Jihun, Kang;Joon-Min, Gil
    • KIPS Transactions on Computer and Communication Systems
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    • v.11 no.11
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    • pp.381-394
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    • 2022
  • Recently, due to the personalization and customization of data, Internet-based services have increased requirements for real-time processing, such as real-time AI inference and data analysis, which must be handled immediately according to the user's situation or requirement. Real-time tasks have a set deadline from the start of each task to the return of the results, and the guarantee of the deadline is directly linked to the quality of the services. However, traditional container systems are limited in operating real-time tasks because they do not provide the ability to allocate and manage deadlines for tasks executed in containers. In addition, tasks such as AI inference and data analysis basically utilize graphical processing units (GPU), which typically have performance impacts on each other because performance isolation is not provided between containers. And the resource usage of the node alone cannot determine the deadline guarantee rate of each container or whether to deploy a new real-time container. In this paper, we propose a monitoring technique for tracking and managing the execution status of deadlines and real-time GPU tasks in containers to support real-time processing of GPU tasks running on containers, and a node list management technique for container placement on appropriate nodes to ensure deadlines. Furthermore, we demonstrate from experiments that the proposed technique has a very small impact on the system.

Performance Analysis of Differential Service Model using Feedback Control (피드백제어를 이용한 차등 서비스 모델의 성능 분석)

  • 백운송;양기원;최영진;김동일;오창석
    • The KIPS Transactions:PartC
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    • v.8C no.1
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    • pp.51-59
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    • 2001
  • In order to support various QoS, IETF has proposed the Differentiated Services Model which provides discrimination service according to t the user’s requirements and payment intention intention for each traffic characteristic. This model is an excellent mechanism, which is not too c complicated in terms of the management for service and network model. Also, it has scalability that satisfies the requirement of Differentiated Services. In this paper, We define the Differentiated Services Model using feedback control, propose its control procedure, and analyze its p performance. In conventional model, non-adaptive traffic, such as UDP traffic, is more occupied the network resource than adaptive traffic, such a as TCP traffic. On the other hand, the Differentiated Services Model using feedback control fairly utlizes the network resources and even p prevents congestion occurrence due to its ability of congestion expectation.

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GPU Memory Management Technique to Improve the Performance of GPGPU Task of Virtual Machines in RPC-Based GPU Virtualization Environments (RPC 기반 GPU 가상화 환경에서 가상머신의 GPGPU 작업 성능 향상을 위한 GPU 메모리 관리 기법)

  • Kang, Jihun
    • KIPS Transactions on Computer and Communication Systems
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    • v.10 no.5
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    • pp.123-136
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    • 2021
  • RPC (Remote Procedure Call)-based Graphics Processing Unit (GPU) virtualization technology is one of the technologies for sharing GPUs with multiple user virtual machines. However, in a cloud environment, unlike CPU or memory, general GPUs do not provide a resource isolation technology that can limit the resource usage of virtual machines. In particular, in an RPC-based virtualization environment, since GPU tasks executed in each virtual machine are performed in the form of multi-process, the lack of resource isolation technology causes performance degradation due to resource competition. In addition, the GPU memory competition accelerates the performance degradation as the resource demand of the virtual machines increases, and the fairness decreases because it cannot guarantee equal performance between virtual machines. This paper, in the RPC-based GPU virtualization environment, analyzes the performance degradation problem caused by resource contention when the GPU memory requirement of virtual machines exceeds the available GPU memory capacity and proposes a GPU memory management technique to solve this problem. Also, experiments show that the GPU memory management technique proposed in this paper can improve the performance of GPGPU tasks.

Early Identification of Gifted Young Children and Dynamic assessment (유아 영재의 판별과 역동적 평가)

  • 장영숙
    • Journal of Gifted/Talented Education
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    • v.11 no.3
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    • pp.131-153
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    • 2001
  • The importance of identifying gifted children during early childhood is becoming recognized. Nonetheless, most researchers preferred to study the primary and secondary levels where children are already and more clearly demonstrating what talents they have, and where more reliable predictions of gifted may be made. Comparatively lisle work has been done in this area. When we identify giftedness during early childhood, we have to consider the potential of the young children rather than on actual achievement. Giftedness during early childhood is still developing and less stable than that of older children and this prevents us from making firm and accurate predictions based on children's actual achievement. Dynamic assessment, based on Vygotsky's concept of the zone of proximal development(ZPD), suggests a new idea in the way the gifted young children are identified. In light of dynamic assessment, for identifying the potential giftedness of young children. we need to involve measuring both unassisted and assisted performance. Dynamic assessment usually consists of a test-intervene-retest format that focuses attention on the improvement in child performance when an adult provides mediated assistance on how to master the testing task. The advantages of the dynamic assessment are as follows: First, the dynamic assessment approach can provide a useful means for assessing young gifted child who have not demonstrated high ability on traditional identification method. Second, the dynamic assessment approach can assess the learning process of young children. Third, the dynamic assessment can lead an individualized education by the early identification of young gifted children. Fourth, the dynamic assessment can be a more accurate predictor of potential by linking diagnosis and instruction. Thus, it can make us provide an educational treatment effectively for young gifted children.

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