• Title/Summary/Keyword: XScale architecture

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Implementation of Worst Case Execution Time Analysis Tool For Embedded Software based on XScale Processor (XScale 프로세서 기반의 임베디드 소프트웨어를 위한 최악실행시간 분석도구의 구현)

  • Park, Hyeon-Hui;Choi, Myeong-Su;Yang, Seung-Min;Choi, Yong-Hoon;Lim, Hyung-Taek
    • The KIPS Transactions:PartA
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    • v.12A no.5 s.95
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    • pp.365-374
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    • 2005
  • Schedulability analysis is necessary to build reliable embedded real-time systems. For schedulability analysis, worst-case execution time(WCET) analysis that computes upper bounds of the execution times of tasks, is required indispensably. WCET analysis is done in two phases. The first phase is high-level analysis that analyzes control flow and finds longest paths of the program. The second phase is low-level analysis that computes execution cycles of basic blocks taking into account the hardware architecture. In this thesis, we design and implement integrated WCET analysis tools. We develop the WCET analysis tools for XScale-based system called WATER(WCET Analysis Tool for Embedded Real-time system). WATER consist of high-level flow analyzer and low-level execution time analyzer. Also, We compare real measurement for execution of program with analysis result calculated by WATER.

An embedded vision system based on an analog VLSI Optical Flow vision sensor

  • Becanovic, Vlatako;Matsuo, Takayuki;Stocker, Alan A.
    • Proceedings of the Korea Society of Information Technology Applications Conference
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    • 2005.11a
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    • pp.285-288
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    • 2005
  • We propose a novel programmable miniature vision module based on a custom designed analog VLSI (aVLSI) chip. The vision module consists of the optical flow vision sensor embedded with commercial off-the-shelves digital hardware; in our case is the Intel XScale PXA270 processor enforced with a programmable gate array device. The aVLSI sensor provides gray-scale imager data as well as smooth optical flow estimates, thus each pixel gives a triplet of information that can be continuously read out as three independent images. The particular computational architecture of the custom designed sensor, which is fully parallel and also analog, allows for efficient real-time estimations of the smooth optical flow. The Intel XScale PXA270 controls the sensor read-out and furthermore allows, together with the programmable gate array, for additional higher level processing of the intensity image and optical flow data. It also provides the necessary standard interface such that the module can be easily programmed and integrated into different vision systems, or even form a complete stand-alone vision system itself. The low power consumption, small size and flexible interface of the proposed vision module suggests that it could be particularly well suited as a vision system in an autonomous robotics platform and especially well suited for educational projects in the robotic sciences.

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Real-time processing system for embedded hardware genetic algorithm (임베디드 하드웨어 유전자 알고리즘을 위한 실시간 처리 시스템)

  • Park Se-hyun;Seo Ki-sung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.8 no.7
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    • pp.1553-1557
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    • 2004
  • A real-time processing system for embedded hardware genetic algorithm is suggested. In order to operate basic module of genetic algorithm in parallel, such as selection, crossover, mutation and evaluation, dual processors based architecture is implemented. The system consists of two Xscale processors and two FPGA with evolvable hardware, which enables to process genetic algorithm efficiently by distributing the computational load of hardware genetic algorithm to each processors equally. The hardware genetic algorithm runs on Linux OS and the resulted chromosome is executed on evolvable hardware in FPGA. Furthermore, the suggested architecture can be extended easily for a couple of connected processors in serial, making it accelerate to compute a real-time hardware genetic algorithm. To investigate the effect of proposed approach, performance comparisons is experimented for an typical computation of genetic algorithm.

Power Prediction of Mobile Processors based on Statistical Analysis of Performance Monitoring Events (성능 모니터링 이벤트들의 통계적 분석에 기반한 모바일 프로세서의 전력 예측)

  • Yun, Hee-Sung;Lee, Sang-Jeong
    • Journal of KIISE:Computing Practices and Letters
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    • v.15 no.7
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    • pp.469-477
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    • 2009
  • In mobile systems, energy efficiency is critical to extend battery life. Therefore, power consumption should be taken into account to develop software in addition to performance, Efficient software design in power and performance is possible if accurate power prediction is accomplished during the execution of software, In this paper, power estimation model is developed using statistical analysis, The proposed model analyzes processor behavior Quantitatively using the data of performance monitoring events and power consumption collected by executing various benchmark programs, And then representative hardware events on power consumption are selected using hierarchical clustering, The power prediction model is established by regression analysis in which the selected events are independent variables and power is a response variable, The proposed model is applied to a PXA320 mobile processor based on Intel XScale architecture and shows average estimation error within 4% of the actual measured power consumption of the processor.

Implementation of a Mobile Robot Control Platform using Real-Time Embedded Linux (실시간 임베디드 리눅스를 이용한 이동 로봇 플랫폼 구현)

  • Choi Byoung-Wook;Shin Eun-Cheol
    • Journal of Institute of Control, Robotics and Systems
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    • v.12 no.2
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    • pp.194-200
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    • 2006
  • The SoC and digital technology development recently enabled the emergence of information devices and control devices because the SoC presents many advantages such like lower power consumption, greater reliability, and lower cost. However, it is nearly impossible to use the SoC without operating systems because the SoC is included with many peripherals and complex architecture. It is required to use embedded operating systems and real-time operating systems may be used as an embedded operating system. So far, real-time operating systems are widely used to implement a Real-Time system since it meets developer's requirements. However, real-time operating systems have disadvantages including a lack of standards, expensive development, and license. Embedded Linux is able to overcome their disadvantages. In this paper, the implementation of control system platform for a mobile robot using real-time Embedded Linux is described. As a control hardware system platform, XScale board is used. As the real-time Embedded Linux, RTAI is adopted which is open source and royalty free, and supports various architectures and real-time devices, such like real-time CAN and real-time COM. This paper shows the implementation of RTAI on XScale board that means the porting procedure. We also applied the control system platform to the mobile robot and compared the Real-Time serial driver with non real-time serial driver. Experimental results show that that using RTAI is useful to build real-time control system with powerful functionalities of Linux.

LRF-Based Servo System for a Manipulator Grasping Moving Cylinders (움직이는 원통형 물체를 잡는 매니퓰레이터를 위한 레이저 거리계 기반의 서보시스템)

  • Cheon, Hong-Seok;Kim, Byung-Kook
    • Journal of Institute of Control, Robotics and Systems
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    • v.14 no.3
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    • pp.263-272
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    • 2008
  • We implemented a real-time servo system for a manipulator based on Laser Range Finder (LRF). and established algorithms for grasping a moving cylinder. We devised a manipulator mechanism and driving hardware based on a system board equipped with Xscale Processor with real-time operating system RTAI on Linux. The manipulator motor driver is connected to the system board via CAN communication link, and LRF is connected via RS-232C. We implemented real-time software including CAN device driver, RS-232C device driver, manipulator trajectory generator, and LRF control software. A typical application experiment for grasping a cylinder with circle motion demonstrated our system's real-time performance.