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    병렬 및 λΆ„μ‚° μž„λ² λ””λ“œ μ‹œμŠ€ν…œμ„ μœ„ν•œ λͺ¨λΈ 기반 μ½”λ“œ 생성 ν”„λ ˆμž„μ›Œν¬

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    ν•™μœ„λ…Όλ¬Έ(박사)--μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› :κ³΅κ³ΌλŒ€ν•™ 컴퓨터곡학뢀,2020. 2. ν•˜μˆœνšŒ.μ†Œν”„νŠΈμ›¨μ–΄ 섀계 생산성 및 μœ μ§€λ³΄μˆ˜μ„±μ„ ν–₯μƒμ‹œν‚€κΈ° μœ„ν•΄ λ‹€μ–‘ν•œ μ†Œν”„νŠΈμ›¨μ–΄ 개발 방법둠이 μ œμ•ˆλ˜μ—ˆμ§€λ§Œ, λŒ€λΆ€λΆ„μ˜ μ—°κ΅¬λŠ” μ‘μš© μ†Œν”„νŠΈμ›¨μ–΄λ₯Ό ν•˜λ‚˜μ˜ ν”„λ‘œμ„Έμ„œμ—μ„œ λ™μž‘μ‹œν‚€λŠ” 데에 μ΄ˆμ μ„ λ§žμΆ”κ³  μžˆλ‹€. λ˜ν•œ, μž„λ² λ””λ“œ μ‹œμŠ€ν…œμ„ κ°œλ°œν•˜λŠ” 데에 ν•„μš”ν•œ μ§€μ—°μ΄λ‚˜ μžμ› μš”κ΅¬ 사항에 λŒ€ν•œ λΉ„κΈ°λŠ₯적 μš”κ΅¬ 사항을 κ³ λ €ν•˜μ§€ μ•Šκ³  있기 λ•Œλ¬Έμ— 일반적인 μ†Œν”„νŠΈμ›¨μ–΄ 개발 방법둠을 μž„λ² λ””λ“œ μ†Œν”„νŠΈμ›¨μ–΄λ₯Ό κ°œλ°œν•˜λŠ” 데에 μ μš©ν•˜λŠ” 것은 μ ν•©ν•˜μ§€ μ•Šλ‹€. 이 λ…Όλ¬Έμ—μ„œλŠ” 병렬 및 λΆ„μ‚° μž„λ² λ””λ“œ μ‹œμŠ€ν…œμ„ λŒ€μƒμœΌλ‘œ ν•˜λŠ” μ†Œν”„νŠΈμ›¨μ–΄λ₯Ό λͺ¨λΈλ‘œ ν‘œν˜„ν•˜κ³ , 이λ₯Ό μ†Œν”„νŠΈμ›¨μ–΄ λΆ„μ„μ΄λ‚˜ κ°œλ°œμ— ν™œμš©ν•˜λŠ” 개발 방법둠을 μ†Œκ°œν•œλ‹€. 우리의 λͺ¨λΈμ—μ„œ μ‘μš© μ†Œν”„νŠΈμ›¨μ–΄λŠ” κ³„μΈ΅μ μœΌλ‘œ ν‘œν˜„ν•  수 μžˆλŠ” μ—¬λŸ¬ 개의 νƒœμŠ€ν¬λ‘œ 이루어져 있으며, ν•˜λ“œμ›¨μ–΄ ν”Œλž«νΌκ³Ό λ…λ¦½μ μœΌλ‘œ λͺ…μ„Έν•œλ‹€. νƒœμŠ€ν¬ κ°„μ˜ 톡신 및 λ™κΈ°ν™”λŠ” λͺ¨λΈμ΄ μ •μ˜ν•œ κ·œμ•½μ΄ μ •ν•΄μ Έ 있고, μ΄λŸ¬ν•œ κ·œμ•½μ„ 톡해 μ‹€μ œ ν”„λ‘œκ·Έλž¨μ„ μ‹€ν–‰ν•˜κΈ° 전에 μ†Œν”„νŠΈμ›¨μ–΄ μ—λŸ¬λ₯Ό 정적 뢄석을 톡해 확인할 수 있고, μ΄λŠ” μ‘μš©μ˜ 검증 λ³΅μž‘λ„λ₯Ό μ€„μ΄λŠ” 데에 κΈ°μ—¬ν•œλ‹€. μ§€μ •ν•œ ν•˜λ“œμ›¨μ–΄ ν”Œλž«νΌμ—μ„œ λ™μž‘ν•˜λŠ” ν”„λ‘œκ·Έλž¨μ€ νƒœμŠ€ν¬λ“€μ„ ν”„λ‘œμ„Έμ„œμ— λ§€ν•‘ν•œ 이후에 μžλ™μ μœΌλ‘œ ν•©μ„±ν•  수 μžˆλ‹€. μœ„μ˜ λͺ¨λΈ 기반 μ†Œν”„νŠΈμ›¨μ–΄ 개발 λ°©λ²•λ‘ μ—μ„œ μ‚¬μš©ν•˜λŠ” ν”„λ‘œκ·Έλž¨ ν•©μ„±κΈ°λ₯Ό λ³Έ λ…Όλ¬Έμ—μ„œ μ œμ•ˆν•˜μ˜€λŠ”λ°, λͺ…μ„Έν•œ ν”Œλž«νΌ μš”κ΅¬ 사항을 λ°”νƒ•μœΌλ‘œ 병렬 및 λΆ„μ‚° μž„λ² λ””λ“œ μ‹œμŠ€ν…œμ„μ—μ„œ λ™μž‘ν•˜λŠ” μ½”λ“œλ₯Ό μƒμ„±ν•œλ‹€. μ—¬λŸ¬ 개의 μ •ν˜•μ  λͺ¨λΈλ“€μ„ κ³„μΈ΅μ μœΌλ‘œ ν‘œν˜„ν•˜μ—¬ μ‘μš©μ˜ 동적 ν–‰νƒœλ₯Ό λ‚˜νƒ€κ³ , ν•©μ„±κΈ°λŠ” μ—¬λŸ¬ λͺ¨λΈλ‘œ κ΅¬μ„±λœ 계측적인 λͺ¨λΈλ‘œλΆ€ν„° 병렬성을 κ³ λ €ν•˜μ—¬ νƒœμŠ€ν¬λ₯Ό μ‹€ν–‰ν•  수 μžˆλ‹€. λ˜ν•œ, ν”„λ‘œκ·Έλž¨ ν•©μ„±κΈ°μ—μ„œ λ‹€μ–‘ν•œ ν”Œλž«νΌμ΄λ‚˜ λ„€νŠΈμ›Œν¬λ₯Ό 지원할 수 μžˆλ„λ‘ μ½”λ“œλ₯Ό κ΄€λ¦¬ν•˜λŠ” 방법도 보여주고 μžˆλ‹€. λ³Έ λ…Όλ¬Έμ—μ„œ μ œμ‹œν•˜λŠ” μ†Œν”„νŠΈμ›¨μ–΄ 개발 방법둠은 6개의 ν•˜λ“œμ›¨μ–΄ ν”Œλž«νΌκ³Ό 3 μ’…λ₯˜μ˜ λ„€νŠΈμ›Œν¬λ‘œ κ΅¬μ„±λ˜μ–΄ μžˆλŠ” μ‹€μ œ κ°μ‹œ μ†Œν”„νŠΈμ›¨μ–΄ μ‹œμŠ€ν…œ μ‘μš© μ˜ˆμ œμ™€ 이쒅 λ©€ν‹° ν”„λ‘œμ„Έμ„œλ₯Ό ν™œμš©ν•˜λŠ” 원격 λ”₯ λŸ¬λ‹ 예제λ₯Ό μˆ˜ν–‰ν•˜μ—¬ 개발 λ°©λ²•λ‘ μ˜ 적용 κ°€λŠ₯성을 μ‹œν—˜ν•˜μ˜€λ‹€. λ˜ν•œ, ν”„λ‘œκ·Έλž¨ ν•©μ„±κΈ°κ°€ μƒˆλ‘œμš΄ ν”Œλž«νΌμ΄λ‚˜ λ„€νŠΈμ›Œν¬λ₯Ό μ§€μ›ν•˜κΈ° μœ„ν•΄ ν•„μš”λ‘œ ν•˜λŠ” 개발 λΉ„μš©λ„ μ‹€μ œ μΈ‘μ • 및 μ˜ˆμΈ‘ν•˜μ—¬ μƒλŒ€μ μœΌλ‘œ 적은 λ…Έλ ₯으둜 μƒˆλ‘œμš΄ ν”Œλž«νΌμ„ 지원할 수 μžˆμŒμ„ ν™•μΈν•˜μ˜€λ‹€. λ§Žμ€ μž„λ² λ””λ“œ μ‹œμŠ€ν…œμ—μ„œ μ˜ˆμƒμΉ˜ λͺ»ν•œ ν•˜λ“œμ›¨μ–΄ μ—λŸ¬μ— λŒ€ν•΄ 결함을 κ°λ‚΄ν•˜λŠ” 것을 ν•„μš”λ‘œ ν•˜κΈ° λ•Œλ¬Έμ— 결함 감내에 λŒ€ν•œ μ½”λ“œλ₯Ό μžλ™μœΌλ‘œ μƒμ„±ν•˜λŠ” 연ꡬ도 μ§„ν–‰ν•˜μ˜€λ‹€. λ³Έ κΈ°λ²•μ—μ„œ 결함 감내 섀정에 따라 νƒœμŠ€ν¬ κ·Έλž˜ν”„λ₯Ό μˆ˜μ •ν•˜λŠ” 방식을 ν™œμš©ν•˜μ˜€μœΌλ©°, 결함 κ°λ‚΄μ˜ λΉ„κΈ°λŠ₯적 μš”κ΅¬ 사항을 μ‘μš© κ°œλ°œμžκ°€ μ‰½κ²Œ μ μš©ν•  수 μžˆλ„λ‘ ν•˜μ˜€λ‹€. λ˜ν•œ, 결함 감내 μ§€μ›ν•˜λŠ” 것과 κ΄€λ ¨ν•˜μ—¬ μ‹€μ œ μˆ˜λ™μœΌλ‘œ κ΅¬ν˜„ν–ˆμ„ κ²½μš°μ™€ λΉ„κ΅ν•˜μ˜€κ³ , 결함 μ£Όμž… 도ꡬλ₯Ό μ΄μš©ν•˜μ—¬ 결함 λ°œμƒ μ‹œλ‚˜λ¦¬μ˜€λ₯Ό μž¬ν˜„ν•˜κ±°λ‚˜, μž„μ˜λ‘œ 결함을 μ£Όμž…ν•˜λŠ” μ‹€ν—˜μ„ μˆ˜ν–‰ν•˜μ˜€λ‹€. λ§ˆμ§€λ§‰μœΌλ‘œ 결함 감내λ₯Ό μ‹€ν—˜ν•  λ•Œμ— ν™œμš©ν•œ 결함 μ£Όμž… λ„κ΅¬λŠ” λ³Έ λ…Όλ¬Έμ˜ 또 λ‹€λ₯Έ κΈ°μ—¬ 사항 쀑 ν•˜λ‚˜λ‘œ λ¦¬λˆ…μŠ€ ν™˜κ²½μœΌλ‘œ λŒ€μƒμœΌλ‘œ μ‘μš© μ˜μ—­ 및 컀널 μ˜μ—­μ— 결함을 μ£Όμž…ν•˜λŠ” 도ꡬλ₯Ό κ°œλ°œν•˜μ˜€λ‹€. μ‹œμŠ€ν…œμ˜ 견고성을 κ²€μ¦ν•˜κΈ° μœ„ν•΄ 결함을 μ£Όμž…ν•˜μ—¬ 결함 μ‹œλ‚˜λ¦¬μ˜€λ₯Ό μž¬ν˜„ν•˜λŠ” 것은 널리 μ‚¬μš©λ˜λŠ” λ°©λ²•μœΌλ‘œ, λ³Έ λ…Όλ¬Έμ—μ„œ 개발된 결함 μ£Όμž… λ„κ΅¬λŠ” μ‹œμŠ€ν…œμ΄ λ™μž‘ν•˜λŠ” 도쀑에 μž¬ν˜„ κ°€λŠ₯ν•œ 결함을 μ£Όμž…ν•  수 μžˆλŠ” 도ꡬ이닀. 컀널 μ˜μ—­μ—μ„œμ˜ 결함 μ£Όμž…μ„ μœ„ν•΄ 두 μ’…λ₯˜μ˜ 결함 μ£Όμž… 방법을 μ œκ³΅ν•˜λ©°, ν•˜λ‚˜λŠ” 컀널 GNU 디버거λ₯Ό μ΄μš©ν•œ 방법이고, λ‹€λ₯Έ ν•˜λ‚˜λŠ” ARM ν•˜λ“œμ›¨μ–΄ 브레이크포인트λ₯Ό ν™œμš©ν•œ 방법이닀. μ‘μš© μ˜μ—­μ—μ„œ 결함을 μ£Όμž…ν•˜κΈ° μœ„ν•΄ GDB 기반 결함 μ£Όμž… 방법을 μ΄μš©ν•˜μ—¬ 동일 μ‹œμŠ€ν…œ ν˜Ήμ€ 원격 μ‹œμŠ€ν…œμ˜ μ‘μš©μ— 결함을 μ£Όμž…ν•  수 μžˆλ‹€. 결함 μ£Όμž… 도ꡬ에 λŒ€ν•œ μ‹€ν—˜μ€ ODROID-XU4 λ³΄λ“œμ—μ„œ μ§„ν–‰ν•˜μ˜€λ‹€.While various software development methodologies have been proposed to increase the design productivity and maintainability of software, they usually focus on the development of application software running on a single processing element, without concern about the non-functional requirements of an embedded system such as latency and resource requirements. In this thesis, we present a model-based software development method for parallel and distributed embedded systems. An application is specified as a set of tasks that follow a set of given rules for communication and synchronization in a hierarchical fashion, independently of the hardware platform. Having such rules enables us to perform static analysis to check some software errors at compile time to reduce the verification difficulty. Platform-specific program is synthesized automatically after mapping of tasks onto processing elements is determined. The program synthesizer is also proposed to generate codes which satisfies platform requirements for parallel and distributed embedded systems. As multiple models which can express dynamic behaviors can be depicted hierarchically, the synthesizer supports to manage multiple task graphs with a different hierarchy to run tasks with parallelism. Also, the synthesizer shows methods of managing codes for heterogeneous platforms and generating various communication methods. The viability of the proposed software development method is verified with a real-life surveillance application that runs on six processing elements with three remote communication methods, and remote deep learning example is conducted to use heterogeneous multiprocessing components on distributed systems. Also, supporting a new platform and network requires a small effort by measuring and estimating development costs. Since tolerance to unexpected errors is a required feature of many embedded systems, we also support an automatic fault-tolerant code generation. Fault tolerance can be applied by modifying the task graph based on the selected fault tolerance configurations, so the non-functional requirement of fault tolerance can be easily adopted by an application developer. To compare the effort of supporting fault tolerance, manual implementation of fault tolerance is performed. Also, the fault tolerance method is tested with the fault injection tool to emulate fault scenarios and inject faults randomly. Our fault injection tool, which has used for testing our fault-tolerance method, is another work of this thesis. Emulating fault scenarios by intentionally injecting faults is commonly used to test and verify the robustness of a system. To emulate faults on an embedded system, we present a run-time fault injection framework that can inject a fault on both a kernel and application layer of Linux-based systems. For injecting faults on a kernel layer, two complementary fault injection techniques are used. One is based on Kernel GNU Debugger, and the other is using a hardware breakpoint supported by the ARM architecture. For application-level fault injection, the GDB-based fault injection method is used to inject a fault on a remote application. The viability of the proposed fault injection tool is proved by real-life experiments with an ODROID-XU4 system.Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Contribution 6 1.3 Dissertation Organization 8 Chapter 2 Background 9 2.1 HOPES: Hope of Parallel Embedded Software 9 2.1.1 Software Development Procedure 9 2.1.2 Components of HOPES 12 2.2 Universal Execution Model 13 2.2.1 Task Graph Specification 13 2.2.2 Dataflow specification of an Application 15 2.2.3 Task Code Specification and Generic APIs 21 2.2.4 Meta-data Specification 23 Chapter 3 Program Synthesis for Parallel and Distributed Embedded Systems 24 3.1 Motivational Example 24 3.2 Program Synthesis Overview 26 3.3 Program Synthesis from Hierarchically-mixed Models 30 3.4 Platform Code Synthesis 33 3.5 Communication Code Synthesis 36 3.6 Experiments 40 3.6.1 Development Cost of Supporting New Platforms and Networks 40 3.6.2 Program Synthesis for the Surveillance System Example 44 3.6.3 Remote GPU-accelerated Deep Learning Example 46 3.7 Document Generation 48 3.8 Related Works 49 Chapter 4 Model Transformation for Fault-tolerant Code Synthesis 56 4.1 Fault-tolerant Code Synthesis Techniques 56 4.2 Applying Fault Tolerance Techniques in HOPES 61 4.3 Experiments 62 4.3.1 Development Cost of Applying Fault Tolerance 62 4.3.2 Fault Tolerance Experiments 62 4.4 Random Fault Injection Experiments 65 4.5 Related Works 68 Chapter 5 Fault Injection Framework for Linux-based Embedded Systems 70 5.1 Background 70 5.1.1 Fault Injection Techniques 70 5.1.2 Kernel GNU Debugger 71 5.1.3 ARM Hardware Breakpoint 72 5.2 Fault Injection Framework 74 5.2.1 Overview 74 5.2.2 Architecture 75 5.2.3 Fault Injection Techniques 79 5.2.4 Implementation 83 5.3 Experiments 90 5.3.1 Experiment Setup 90 5.3.2 Performance Comparison of Two Fault Injection Methods 90 5.3.3 Bit-flip Fault Experiments 92 5.3.4 eMMC Controller Fault Experiments 94 Chapter 6 Conclusion 97 Bibliography 99 μš” μ•½ 108Docto

    Integrated Design and Implementation of Embedded Control Systems with Scilab

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    Embedded systems are playing an increasingly important role in control engineering. Despite their popularity, embedded systems are generally subject to resource constraints and it is therefore difficult to build complex control systems on embedded platforms. Traditionally, the design and implementation of control systems are often separated, which causes the development of embedded control systems to be highly time-consuming and costly. To address these problems, this paper presents a low-cost, reusable, reconfigurable platform that enables integrated design and implementation of embedded control systems. To minimize the cost, free and open source software packages such as Linux and Scilab are used. Scilab is ported to the embedded ARM-Linux system. The drivers for interfacing Scilab with several communication protocols including serial, Ethernet, and Modbus are developed. Experiments are conducted to test the developed embedded platform. The use of Scilab enables implementation of complex control algorithms on embedded platforms. With the developed platform, it is possible to perform all phases of the development cycle of embedded control systems in a unified environment, thus facilitating the reduction of development time and cost.Comment: 15 pages, 14 figures; Open Access at http://www.mdpi.org/sensors/papers/s8095501.pd

    Developing a distributed electronic health-record store for India

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    The DIGHT project is addressing the problem of building a scalable and highly available information store for the Electronic Health Records (EHRs) of the over one billion citizens of India

    Embedding Multi-Task Address-Event- Representation Computation

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    Address-Event-Representation, AER, is a communication protocol that is intended to transfer neuronal spikes between bioinspired chips. There are several AER tools to help to develop and test AER based systems, which may consist of a hierarchical structure with several chips that transmit spikes among them in real-time, while performing some processing. Although these tools reach very high bandwidth at the AER communication level, they require the use of a personal computer to allow the higher level processing of the event information. We propose the use of an embedded platform based on a multi-task operating system to allow both, the AER communication and processing without the requirement of either a laptop or a computer. In this paper, we present and study the performance of an embedded multi-task AER tool, connecting and programming it for processing Address-Event information from a spiking generator.Ministerio de Ciencia e InnovaciΓ³n TEC2006-11730-C03-0
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