3 research outputs found
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λꡬμ λν μ€νμ ODROID-XU4 보λμμ μ§ννμλ€.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
μ μ½ 108Docto
A Code Generation Framework for Actor-Oriented Models with Partial Evaluation
Abstract. Embedded software requires concurrency formalisms other than threads and mutexes used in traditional programming languages like C. Actor-oriented design presents a high level abstraction for composing concurrent components. However, high level abstraction often introduces overhead and results in slower system. We address the problem of generating efficient implementation for the systems with such a high level description. We use partial evaluation as an optimized compilation technique for actor-oriented models. We use a helper-based mechanism, which results in flexible and extensible code generation framework. The end result is that the benefit offered by high level abstraction comes with (almost) no performance penalty. The code generation framework has been released in open source form as part of Ptolemy II 6.0.1.