• Title/Summary/Keyword: Heterogeneous-Computing

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Collaborative Streamlined On-Chip Software Architecture on Heterogenous Multi-Cores for Low-Power Reactive Control in Automotive Embedded Processors (차량용 임베디드 프로세서에서 저전력 반응적 제어를 위한 이기종 멀티코어 협력적 스트리밍 온-칩 소프트웨어 구조)

  • Jisu, Kwon;Daejin, Park
    • IEMEK Journal of Embedded Systems and Applications
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    • v.17 no.6
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    • pp.375-382
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    • 2022
  • This paper proposes a multi-core cooperative computing structure considering the heterogeneous features of automotive embedded on-chip software. The automotive embedded software has the heterogeneous execution flow properties for various hardware drives. Software developed with a homogeneous execution flow without considering these properties will incur inefficient overhead due to core latency and load. The proposed method was evaluated on an target board on which a automotive MCU (micro-controller unit) with built-in multi-cores was mounted. We demonstrate an overhead reduction when software including common embedded system tasks, such as ADC sampling, DSP operations, and communication interfaces, are implemented in a heterogeneous execution flow. When we used the proposed method, embedded software was able to take advantage of idle states that occur between heterogeneous tasks to make efficient use of the resources on the board. As a result of the experiments, the power consumption of the board decreased by 42.11% compared to the baseline. Furthermore, the time required to process the same amount of sampling data was reduced by 27.09%. Experimental results validate the efficiency of the proposed multi-core cooperative heterogeneous embedded software execution technique.

An Efficient Scheduling Method for Grid Systems Based on a Hierarchical Stochastic Petri Net

  • Shojafar, Mohammad;Pooranian, Zahra;Abawajy, Jemal H.;Meybodi, Mohammad Reza
    • Journal of Computing Science and Engineering
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    • v.7 no.1
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    • pp.44-52
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    • 2013
  • This paper addresses the problem of resource scheduling in a grid computing environment. One of the main goals of grid computing is to share system resources among geographically dispersed users, and schedule resource requests in an efficient manner. Grid computing resources are distributed, heterogeneous, dynamic, and autonomous, which makes resource scheduling a complex problem. This paper proposes a new approach to resource scheduling in grid computing environments, the hierarchical stochastic Petri net (HSPN). The HSPN optimizes grid resource sharing, by categorizing resource requests in three layers, where each layer has special functions for receiving subtasks from, and delivering data to, the layer above or below. We compare the HSPN performance with the Min-min and Max-min resource scheduling algorithms. Our results show that the HSPN performs better than Max-min, but slightly underperforms Min-min.

An Efficient Approach for Computer Integrated Manufacturing Database Using Neural Network (신경망을 이용한 CIM 데이터베이스의 효율적인 처리 방법)

  • 김선희;김국보;정환묵
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1996.10a
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    • pp.223-226
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    • 1996
  • One of the consideration issue in implementation and maintanence of CIM(Computer Integrated Manufacturing) database is exchange and sharing of information between heterogeneous databases. For efficient operating of SIM systems, it must be able to organize and to manage the information. In this paper, we propose method that can make enhance the efficiency of CIM database, classfying the data in database using self organize neural network to each database systems, and computing between classfied heterogeneous database using extended operator that is defined.

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Development of Virtual Parallel Processing System for Flexible Task Allocation on the Web (웹 환경에서 유연성 있는 작업 할당을 위한 가상 병렬 처리 시스템 개발)

  • 정권호;송은하;정영식
    • Journal of Korea Multimedia Society
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    • v.3 no.3
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    • pp.320-332
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    • 2000
  • Web consists of the grand virtual system which is made of all connected computers network. We can solve the huge problem which requires high quality in cost performance and powerful computing power to use a numerous idle state system on internet as process it parallel. However, we have to consider heterogeneous computing resources, accessibility, and reliability to carry out parallel system on global environment, not network but whole Internet. In this paper, We the WebImg system which has the power of web computing, and show the flexible task allocation strategy in heterogeneous hosts. Also, we evaluate its performance, moreover the proposed task allocation strategy supplies fault tolerance by controlling host situation at any time.

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A Scheduling Algorithm for Parsing of MPEG Video on the Heterogeneous Distributed Environment (이질적인 분산 환경에서의 MPEG비디오의 파싱을 위한 스케줄링 알고리즘)

  • Nam Yunyoung;Hwang Eenjun
    • Journal of KIISE:Computer Systems and Theory
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    • v.31 no.12
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    • pp.673-681
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    • 2004
  • As the use of digital videos is getting popular, there is an increasing demand for efficient browsing and retrieval of video. To support such operations, effective video indexing should be incorporated. One of the most fundamental steps in video indexing is to parse video stream into shots and scenes. Generally, it takes long time to parse a video due to the huge amount of computation in a traditional single computing environment. Previous studies had widely used Round Robin scheduling which basically allocates tasks to each slave for a time interval of one quantum. This scheduling is difficult to adapt in a heterogeneous environment. In this paper, we propose two different parallel parsing algorithms which are Size-Adaptive Round Robin and Dynamic Size-Adaptive Round Robin for the heterogeneous distributed computing environments. In order to show their performance, we perform several experiments and show some of the results.

Security and Privacy Mechanism using TCG/TPM to various WSN (다양한 무선네트워크 하에서 TCG/TPM을 이용한 정보보호 및 프라이버시 매커니즘)

  • Lee, Ki-Man;Cho, Nae-Hyun;Kwon, Hwan-Woo;Seo, Chang-Ho
    • Journal of the Korea Society of Computer and Information
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    • v.13 no.5
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    • pp.195-202
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    • 2008
  • In this paper, To improve the effectiveness of security enforcement, the first contribution in this work is that we present a clustered heterogeneous WSN(Wareless Sensor Network) architecture, composed of not only resource constrained sensor nodes, but also a number of more powerful high-end devices acting as cluster heads. Compared to sensor nodes, a high-end cluster head has higher computation capability, larger storage, longer power supply, and longer radio transmission range, and it thus does not suffer from the resource scarceness problem as much as a sensor node does. A distinct feature of our heterogeneous architecture is that cluster heads are equipped with TC(trusted computing) technology, and in particular a TCG(Trusted Computing Group) compliant TPM (Trusted Platform Module) is embedded into each cluster head. According the TCG specifications, TPM is a tamper-resistant, self-contained secure coprocessor, capable of performing cryptographic functions. A TPM attached to a host establishes a trusted computing platform that provides sealed storage, and measures and reports the integrity state of the platform.

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Implementation of Exchange Rate Forecasting Neural Network Using Heterogeneous Computing (이기종 컴퓨팅을 활용한 환율 예측 뉴럴 네트워크 구현)

  • Han, Seong Hyeon;Lee, Kwang Yeob
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.7 no.11
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    • pp.71-79
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    • 2017
  • In this paper, we implemented the exchange rate forecasting neural network using heterogeneous computing. Exchange rate forecasting requires a large amount of data. We used a neural network that could leverage this data accordingly. Neural networks are largely divided into two processes: learning and verification. Learning took advantage of the CPU. For verification, RTL written in Verilog HDL was run on FPGA. The structure of the neural network has four input neurons, four hidden neurons, and one output neuron. The input neurons used the US $ 1, Japanese 100 Yen, EU 1 Euro, and UK £ 1. The input neurons predicted a Canadian dollar value of $ 1. The order of predicting the exchange rate is input, normalization, fixed-point conversion, neural network forward, floating-point conversion, denormalization, and outputting. As a result of forecasting the exchange rate in November 2016, there was an error amount between 0.9 won and 9.13 won. If we increase the number of neurons by adding data other than the exchange rate, it is expected that more precise exchange rate prediction will be possible.

Design and Implementation of National Supercomputing Service Framework (국가 슈퍼컴퓨팅 서비스 프레임워크의 설계 및 구현)

  • Yu, Jung-Lok;Byun, Hee-Jung;Kim, Han-Gi
    • KIISE Transactions on Computing Practices
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    • v.22 no.12
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    • pp.663-674
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    • 2016
  • Traditional supercomputing services suffer from limited accessibility and low utilization in that users(researchers) may perform computational executions only using terminal-based command line interfaces. To address this problem, in this paper, we provide the design and implementation details of National supercomputing service framework. The proposed framework supports all the fundamental primitive functions such as user management/authentication, heterogeneous computing resource management, HPC (High Performance Computing) job management, etc. so that it enables various 3rd-party applications to be newly built on top of the proposed framework. Our framework also provides Web-based RESTful OpenAPIs and the abstraction interfaces of job schedulers (as well as bundle scheduler plug-ins, for example, LoadLeveler, Open Grid Scheduler, TORQUE) in order to easily integrate the broad spectrum of heterogeneous computing clusters. To show and validate the effectiveness of the proposed framework, we describe the best practice scenario of high energy physics Lattice-QCD as an example application.

A Two-Step Job Scheduling Algorithm Based on Priority for Cloud Computing

  • Kim, Jeongwon
    • Journal of information and communication convergence engineering
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    • v.11 no.4
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    • pp.235-240
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    • 2013
  • Cloud systems are popular computing environment because they can provide easy access to computing resources for users as well as efficient use of resources for companies. The resources of cloud computing are heterogeneous and jobs have various characteristics. One such issue is effective job scheduling. Scheduling in the cloud system may be defined as a multiple criteria decision model. To address this issue, this paper proposes a priority-based two-step job scheduling algorithm. On the first level, jobs are classified based on preference. Resources are dedicated to a job if a deadline failure would cause severe results or critical business losses. In case of only minor discomfort or slight functional impairment, the job is scheduled using a best effort approach. On the second level, jobs are allocated to adequate resources through their priorities that are calculated by the analytic hierarchic process model. We then analyze the proposed algorithm and make a scheduling example to confirm its efficiency.

Middleware Architecture for Open Control Systems in the Distributed Computing Environment

  • Lee, Wongoo;Park, Jaehyun
    • Transactions on Control, Automation and Systems Engineering
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    • v.3 no.3
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    • pp.190-195
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    • 2001
  • The advance of computer, network, and Internet technology enables the control systems to process the massive data in the distributed computing environments. To implement and maintain the software in distributed environment, the component-based methodology is widely used. This paper proposes the middleware architecture for the distributed computer control system. With the proposed middleware services, it is relatively easy to maintain compatibility between products and to implement a portable control application. To achieve the compatibility between heterogeneous systems, the proposed architecture provides the communication protocols based on the XML with lightweight event-based service.

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