2,074 research outputs found

    Optimizing construction of scheduled data flow graph for on-line testability

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    The objective of this work is to develop a new methodology for behavioural synthesis using a flow of synthesis, better suited to the scheduling of independent calculations and non-concurrent online testing. The traditional behavioural synthesis process can be defined as the compilation of an algorithmic specification into an architecture composed of a data path and a controller. This stream of synthesis generally involves scheduling, resource allocation, generation of the data path and controller synthesis. Experiments showed that optimization started at the high level synthesis improves the performance of the result, yet the current tools do not offer synthesis optimizations that from the RTL level. This justifies the development of an optimization methodology which takes effect from the behavioural specification and accompanying the synthesis process in its various stages. In this paper we propose the use of algebraic properties (commutativity, associativity and distributivity) to transform readable mathematical formulas of algorithmic specifications into mathematical formulas evaluated efficiently. This will effectively reduce the execution time of scheduling calculations and increase the possibilities of testability

    Efficient Simulation of Structural Faults for the Reliability Evaluation at System-Level

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    In recent technology nodes, reliability is considered a part of the standard design ยฟow at all levels of embedded system design. While techniques that use only low-level models at gate- and register transfer-level offer high accuracy, they are too inefficient to consider the overall application of the embedded system. Multi-level models with high abstraction are essential to efficiently evaluate the impact of physical defects on the system. This paper provides a methodology that leverages state-of-the-art techniques for efficient fault simulation of structural faults together with transaction-level modeling. This way it is possible to accurately evaluate the impact of the faults on the entire hardware/software system. A case study of a system consisting of hardware and software for image compression and data encryption is presented and the method is compared to a standard gate/RT mixed-level approac

    Programming MPSoC platforms: Road works ahead

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    This paper summarizes a special session on multicore/multi-processor system-on-chip (MPSoC) programming challenges. The current trend towards MPSoC platforms in most computing domains does not only mean a radical change in computer architecture. Even more important from a SW developerยดs viewpoint, at the same time the classical sequential von Neumann programming model needs to be overcome. Efficient utilization of the MPSoC HW resources demands for radically new models and corresponding SW development tools, capable of exploiting the available parallelism and guaranteeing bug-free parallel SW. While several standards are established in the high-performance computing domain (e.g. OpenMP), it is clear that more innovations are required for successful\ud deployment of heterogeneous embedded MPSoC. On the other hand, at least for coming years, the freedom for disruptive programming technologies is limited by the huge amount of certified sequential code that demands for a more pragmatic, gradual tool and code replacement strategy

    Safety-related challenges and opportunities for GPUs in the automotive domain

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    GPUs have been shown to cover the computing performance needs of autonomous driving (AD) systems. However, since the GPUs used for AD build on designs for the mainstream market, they may lack fundamental properties for correct operation under automotive's safety regulations. In this paper, we analyze some of the main challenges in hardware and software design to embrace GPUs as the reference computing solution for AD, with the emphasis in ISO 26262 functional safety requirements.Authors would like to thank Guillem Bernat from Rapita Systems for his technical feedback on this work. The research leading to this work has received funding from the European Re-search Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 772773). This work has also been partially supported by the Spanish Ministry of Science and Innovation under grant TIN2015-65316-P and the HiPEAC Network of Excellence. Jaume Abella has been partially supported by the Ministry of Economy and Competitiveness under Ramon y Cajal postdoctoral fellowship number RYC-2013-14717. Carles Hernรกndez is jointly funded by the Spanish Ministry of Economy and Competitiveness and FEDER funds through grant TIN2014-60404-JIN.Peer ReviewedPostprint (author's final draft

    The HdpH DSLs for scalable reliable computation

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    The statelessness of functional computations facilitates both parallelism and fault recovery. Faults and non-uniform communication topologies are key challenges for emergent large scale parallel architectures. We report on HdpH and HdpH-RS, a pair of Haskell DSLs designed to address these challenges for irregular task-parallel computations on large distributed-memory architectures. Both DSLs share an API combining explicit task placement with sophisticated work stealing. HdpH focuses on scalability by making placement and stealing topology aware whereas HdpH-RS delivers reliability by means of fault tolerant work stealing. We present operational semantics for both DSLs and investigate conditions for semantic equivalence of HdpH and HdpH-RS programs, that is, conditions under which topology awareness can be transparently traded for fault tolerance. We detail how the DSL implementations realise topology awareness and fault tolerance. We report an initial evaluation of scalability and fault tolerance on a 256-core cluster and on up to 32K cores of an HPC platform

    Design and Test Space Exploration of Transport-Triggered Architectures

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    This paper describes a new approach in the high level design and test of transport-triggered architectures (TTA), a special type of application specific instruction processors (ASIP). The proposed method introduces the test as an additional constraint, besides throughput and circuit area. The method, that calculates the testability of the system, helps the designer to assess the obtained architectures with respect to test, area and throughput in the early phase of the design and selects the most suitable one. In order to create the templated TTA, the ยฟMOVEยฟ framework has been addressed. The approach is validated with respect to the ยฟCryptยฟ Unix applicatio

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๊ณต๊ณผ๋Œ€ํ•™ ์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€,2020. 2. ํ•˜์ˆœํšŒ.์†Œํ”„ํŠธ์›จ์–ด ์„ค๊ณ„ ์ƒ์‚ฐ์„ฑ ๋ฐ ์œ ์ง€๋ณด์ˆ˜์„ฑ์„ ํ–ฅ์ƒ์‹œํ‚ค๊ธฐ ์œ„ํ•ด ๋‹ค์–‘ํ•œ ์†Œํ”„ํŠธ์›จ์–ด ๊ฐœ๋ฐœ ๋ฐฉ๋ฒ•๋ก ์ด ์ œ์•ˆ๋˜์—ˆ์ง€๋งŒ, ๋Œ€๋ถ€๋ถ„์˜ ์—ฐ๊ตฌ๋Š” ์‘์šฉ ์†Œํ”„ํŠธ์›จ์–ด๋ฅผ ํ•˜๋‚˜์˜ ํ”„๋กœ์„ธ์„œ์—์„œ ๋™์ž‘์‹œํ‚ค๋Š” ๋ฐ์— ์ดˆ์ ์„ ๋งž์ถ”๊ณ  ์žˆ๋‹ค. ๋˜ํ•œ, ์ž„๋ฒ ๋””๋“œ ์‹œ์Šคํ…œ์„ ๊ฐœ๋ฐœํ•˜๋Š” ๋ฐ์— ํ•„์š”ํ•œ ์ง€์—ฐ์ด๋‚˜ ์ž์› ์š”๊ตฌ ์‚ฌํ•ญ์— ๋Œ€ํ•œ ๋น„๊ธฐ๋Šฅ์  ์š”๊ตฌ ์‚ฌํ•ญ์„ ๊ณ ๋ คํ•˜์ง€ ์•Š๊ณ  ์žˆ๊ธฐ ๋•Œ๋ฌธ์— ์ผ๋ฐ˜์ ์ธ ์†Œํ”„ํŠธ์›จ์–ด ๊ฐœ๋ฐœ ๋ฐฉ๋ฒ•๋ก ์„ ์ž„๋ฒ ๋””๋“œ ์†Œํ”„ํŠธ์›จ์–ด๋ฅผ ๊ฐœ๋ฐœํ•˜๋Š” ๋ฐ์— ์ ์šฉํ•˜๋Š” ๊ฒƒ์€ ์ ํ•ฉํ•˜์ง€ ์•Š๋‹ค. ์ด ๋…ผ๋ฌธ์—์„œ๋Š” ๋ณ‘๋ ฌ ๋ฐ ๋ถ„์‚ฐ ์ž„๋ฒ ๋””๋“œ ์‹œ์Šคํ…œ์„ ๋Œ€์ƒ์œผ๋กœ ํ•˜๋Š” ์†Œํ”„ํŠธ์›จ์–ด๋ฅผ ๋ชจ๋ธ๋กœ ํ‘œํ˜„ํ•˜๊ณ , ์ด๋ฅผ ์†Œํ”„ํŠธ์›จ์–ด ๋ถ„์„์ด๋‚˜ ๊ฐœ๋ฐœ์— ํ™œ์šฉํ•˜๋Š” ๊ฐœ๋ฐœ ๋ฐฉ๋ฒ•๋ก ์„ ์†Œ๊ฐœํ•œ๋‹ค. ์šฐ๋ฆฌ์˜ ๋ชจ๋ธ์—์„œ ์‘์šฉ ์†Œํ”„ํŠธ์›จ์–ด๋Š” ๊ณ„์ธต์ ์œผ๋กœ ํ‘œํ˜„ํ•  ์ˆ˜ ์žˆ๋Š” ์—ฌ๋Ÿฌ ๊ฐœ์˜ ํƒœ์Šคํฌ๋กœ ์ด๋ฃจ์–ด์ ธ ์žˆ์œผ๋ฉฐ, ํ•˜๋“œ์›จ์–ด ํ”Œ๋žซํผ๊ณผ ๋…๋ฆฝ์ ์œผ๋กœ ๋ช…์„ธํ•œ๋‹ค. ํƒœ์Šคํฌ ๊ฐ„์˜ ํ†ต์‹  ๋ฐ ๋™๊ธฐํ™”๋Š” ๋ชจ๋ธ์ด ์ •์˜ํ•œ ๊ทœ์•ฝ์ด ์ •ํ•ด์ ธ ์žˆ๊ณ , ์ด๋Ÿฌํ•œ ๊ทœ์•ฝ์„ ํ†ตํ•ด ์‹ค์ œ ํ”„๋กœ๊ทธ๋žจ์„ ์‹คํ–‰ํ•˜๊ธฐ ์ „์— ์†Œํ”„ํŠธ์›จ์–ด ์—๋Ÿฌ๋ฅผ ์ •์  ๋ถ„์„์„ ํ†ตํ•ด ํ™•์ธํ•  ์ˆ˜ ์žˆ๊ณ , ์ด๋Š” ์‘์šฉ์˜ ๊ฒ€์ฆ ๋ณต์žก๋„๋ฅผ ์ค„์ด๋Š” ๋ฐ์— ๊ธฐ์—ฌํ•œ๋‹ค. ์ง€์ •ํ•œ ํ•˜๋“œ์›จ์–ด ํ”Œ๋žซํผ์—์„œ ๋™์ž‘ํ•˜๋Š” ํ”„๋กœ๊ทธ๋žจ์€ ํƒœ์Šคํฌ๋“ค์„ ํ”„๋กœ์„ธ์„œ์— ๋งคํ•‘ํ•œ ์ดํ›„์— ์ž๋™์ ์œผ๋กœ ํ•ฉ์„ฑํ•  ์ˆ˜ ์žˆ๋‹ค. ์œ„์˜ ๋ชจ๋ธ ๊ธฐ๋ฐ˜ ์†Œํ”„ํŠธ์›จ์–ด ๊ฐœ๋ฐœ ๋ฐฉ๋ฒ•๋ก ์—์„œ ์‚ฌ์šฉํ•˜๋Š” ํ”„๋กœ๊ทธ๋žจ ํ•ฉ์„ฑ๊ธฐ๋ฅผ ๋ณธ ๋…ผ๋ฌธ์—์„œ ์ œ์•ˆํ•˜์˜€๋Š”๋ฐ, ๋ช…์„ธํ•œ ํ”Œ๋žซํผ ์š”๊ตฌ ์‚ฌํ•ญ์„ ๋ฐ”ํƒ•์œผ๋กœ ๋ณ‘๋ ฌ ๋ฐ ๋ถ„์‚ฐ ์ž„๋ฒ ๋””๋“œ ์‹œ์Šคํ…œ์„์—์„œ ๋™์ž‘ํ•˜๋Š” ์ฝ”๋“œ๋ฅผ ์ƒ์„ฑํ•œ๋‹ค. ์—ฌ๋Ÿฌ ๊ฐœ์˜ ์ •ํ˜•์  ๋ชจ๋ธ๋“ค์„ ๊ณ„์ธต์ ์œผ๋กœ ํ‘œํ˜„ํ•˜์—ฌ ์‘์šฉ์˜ ๋™์  ํ–‰ํƒœ๋ฅผ ๋‚˜ํƒ€๊ณ , ํ•ฉ์„ฑ๊ธฐ๋Š” ์—ฌ๋Ÿฌ ๋ชจ๋ธ๋กœ ๊ตฌ์„ฑ๋œ ๊ณ„์ธต์ ์ธ ๋ชจ๋ธ๋กœ๋ถ€ํ„ฐ ๋ณ‘๋ ฌ์„ฑ์„ ๊ณ ๋ คํ•˜์—ฌ ํƒœ์Šคํฌ๋ฅผ ์‹คํ–‰ํ•  ์ˆ˜ ์žˆ๋‹ค. ๋˜ํ•œ, ํ”„๋กœ๊ทธ๋žจ ํ•ฉ์„ฑ๊ธฐ์—์„œ ๋‹ค์–‘ํ•œ ํ”Œ๋žซํผ์ด๋‚˜ ๋„คํŠธ์›Œํฌ๋ฅผ ์ง€์›ํ•  ์ˆ˜ ์žˆ๋„๋ก ์ฝ”๋“œ๋ฅผ ๊ด€๋ฆฌํ•˜๋Š” ๋ฐฉ๋ฒ•๋„ ๋ณด์—ฌ์ฃผ๊ณ  ์žˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ ์ œ์‹œํ•˜๋Š” ์†Œํ”„ํŠธ์›จ์–ด ๊ฐœ๋ฐœ ๋ฐฉ๋ฒ•๋ก ์€ 6๊ฐœ์˜ ํ•˜๋“œ์›จ์–ด ํ”Œ๋žซํผ๊ณผ 3 ์ข…๋ฅ˜์˜ ๋„คํŠธ์›Œํฌ๋กœ ๊ตฌ์„ฑ๋˜์–ด ์žˆ๋Š” ์‹ค์ œ ๊ฐ์‹œ ์†Œํ”„ํŠธ์›จ์–ด ์‹œ์Šคํ…œ ์‘์šฉ ์˜ˆ์ œ์™€ ์ด์ข… ๋ฉ€ํ‹ฐ ํ”„๋กœ์„ธ์„œ๋ฅผ ํ™œ์šฉํ•˜๋Š” ์›๊ฒฉ ๋”ฅ ๋Ÿฌ๋‹ ์˜ˆ์ œ๋ฅผ ์ˆ˜ํ–‰ํ•˜์—ฌ ๊ฐœ๋ฐœ ๋ฐฉ๋ฒ•๋ก ์˜ ์ ์šฉ ๊ฐ€๋Šฅ์„ฑ์„ ์‹œํ—˜ํ•˜์˜€๋‹ค. ๋˜ํ•œ, ํ”„๋กœ๊ทธ๋žจ ํ•ฉ์„ฑ๊ธฐ๊ฐ€ ์ƒˆ๋กœ์šด ํ”Œ๋žซํผ์ด๋‚˜ ๋„คํŠธ์›Œํฌ๋ฅผ ์ง€์›ํ•˜๊ธฐ ์œ„ํ•ด ํ•„์š”๋กœ ํ•˜๋Š” ๊ฐœ๋ฐœ ๋น„์šฉ๋„ ์‹ค์ œ ์ธก์ • ๋ฐ ์˜ˆ์ธกํ•˜์—ฌ ์ƒ๋Œ€์ ์œผ๋กœ ์ ์€ ๋…ธ๋ ฅ์œผ๋กœ ์ƒˆ๋กœ์šด ํ”Œ๋žซํผ์„ ์ง€์›ํ•  ์ˆ˜ ์žˆ์Œ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋งŽ์€ ์ž„๋ฒ ๋””๋“œ ์‹œ์Šคํ…œ์—์„œ ์˜ˆ์ƒ์น˜ ๋ชปํ•œ ํ•˜๋“œ์›จ์–ด ์—๋Ÿฌ์— ๋Œ€ํ•ด ๊ฒฐํ•จ์„ ๊ฐ๋‚ดํ•˜๋Š” ๊ฒƒ์„ ํ•„์š”๋กœ ํ•˜๊ธฐ ๋•Œ๋ฌธ์— ๊ฒฐํ•จ ๊ฐ๋‚ด์— ๋Œ€ํ•œ ์ฝ”๋“œ๋ฅผ ์ž๋™์œผ๋กœ ์ƒ์„ฑํ•˜๋Š” ์—ฐ๊ตฌ๋„ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ๋ณธ ๊ธฐ๋ฒ•์—์„œ ๊ฒฐํ•จ ๊ฐ๋‚ด ์„ค์ •์— ๋”ฐ๋ผ ํƒœ์Šคํฌ ๊ทธ๋ž˜ํ”„๋ฅผ ์ˆ˜์ •ํ•˜๋Š” ๋ฐฉ์‹์„ ํ™œ์šฉํ•˜์˜€์œผ๋ฉฐ, ๊ฒฐํ•จ ๊ฐ๋‚ด์˜ ๋น„๊ธฐ๋Šฅ์  ์š”๊ตฌ ์‚ฌํ•ญ์„ ์‘์šฉ ๊ฐœ๋ฐœ์ž๊ฐ€ ์‰ฝ๊ฒŒ ์ ์šฉํ•  ์ˆ˜ ์žˆ๋„๋ก ํ•˜์˜€๋‹ค. ๋˜ํ•œ, ๊ฒฐํ•จ ๊ฐ๋‚ด ์ง€์›ํ•˜๋Š” ๊ฒƒ๊ณผ ๊ด€๋ จํ•˜์—ฌ ์‹ค์ œ ์ˆ˜๋™์œผ๋กœ ๊ตฌํ˜„ํ–ˆ์„ ๊ฒฝ์šฐ์™€ ๋น„๊ตํ•˜์˜€๊ณ , ๊ฒฐํ•จ ์ฃผ์ž… ๋„๊ตฌ๋ฅผ ์ด์šฉํ•˜์—ฌ ๊ฒฐํ•จ ๋ฐœ์ƒ ์‹œ๋‚˜๋ฆฌ์˜ค๋ฅผ ์žฌํ˜„ํ•˜๊ฑฐ๋‚˜, ์ž„์˜๋กœ ๊ฒฐํ•จ์„ ์ฃผ์ž…ํ•˜๋Š” ์‹คํ—˜์„ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ๊ฒฐํ•จ ๊ฐ๋‚ด๋ฅผ ์‹คํ—˜ํ•  ๋•Œ์— ํ™œ์šฉํ•œ ๊ฒฐํ•จ ์ฃผ์ž… ๋„๊ตฌ๋Š” ๋ณธ ๋…ผ๋ฌธ์˜ ๋˜ ๋‹ค๋ฅธ ๊ธฐ์—ฌ ์‚ฌํ•ญ ์ค‘ ํ•˜๋‚˜๋กœ ๋ฆฌ๋ˆ…์Šค ํ™˜๊ฒฝ์œผ๋กœ ๋Œ€์ƒ์œผ๋กœ ์‘์šฉ ์˜์—ญ ๋ฐ ์ปค๋„ ์˜์—ญ์— ๊ฒฐํ•จ์„ ์ฃผ์ž…ํ•˜๋Š” ๋„๊ตฌ๋ฅผ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ์‹œ์Šคํ…œ์˜ ๊ฒฌ๊ณ ์„ฑ์„ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•ด ๊ฒฐํ•จ์„ ์ฃผ์ž…ํ•˜์—ฌ ๊ฒฐํ•จ ์‹œ๋‚˜๋ฆฌ์˜ค๋ฅผ ์žฌํ˜„ํ•˜๋Š” ๊ฒƒ์€ ๋„๋ฆฌ ์‚ฌ์šฉ๋˜๋Š” ๋ฐฉ๋ฒ•์œผ๋กœ, ๋ณธ ๋…ผ๋ฌธ์—์„œ ๊ฐœ๋ฐœ๋œ ๊ฒฐํ•จ ์ฃผ์ž… ๋„๊ตฌ๋Š” ์‹œ์Šคํ…œ์ด ๋™์ž‘ํ•˜๋Š” ๋„์ค‘์— ์žฌํ˜„ ๊ฐ€๋Šฅํ•œ ๊ฒฐํ•จ์„ ์ฃผ์ž…ํ•  ์ˆ˜ ์žˆ๋Š” ๋„๊ตฌ์ด๋‹ค. ์ปค๋„ ์˜์—ญ์—์„œ์˜ ๊ฒฐํ•จ ์ฃผ์ž…์„ ์œ„ํ•ด ๋‘ ์ข…๋ฅ˜์˜ ๊ฒฐํ•จ ์ฃผ์ž… ๋ฐฉ๋ฒ•์„ ์ œ๊ณตํ•˜๋ฉฐ, ํ•˜๋‚˜๋Š” ์ปค๋„ GNU ๋””๋ฒ„๊ฑฐ๋ฅผ ์ด์šฉํ•œ ๋ฐฉ๋ฒ•์ด๊ณ , ๋‹ค๋ฅธ ํ•˜๋‚˜๋Š” ARM ํ•˜๋“œ์›จ์–ด ๋ธŒ๋ ˆ์ดํฌํฌ์ธํŠธ๋ฅผ ํ™œ์šฉํ•œ ๋ฐฉ๋ฒ•์ด๋‹ค. ์‘์šฉ ์˜์—ญ์—์„œ ๊ฒฐํ•จ์„ ์ฃผ์ž…ํ•˜๊ธฐ ์œ„ํ•ด GDB ๊ธฐ๋ฐ˜ ๊ฒฐํ•จ ์ฃผ์ž… ๋ฐฉ๋ฒ•์„ ์ด์šฉํ•˜์—ฌ ๋™์ผ ์‹œ์Šคํ…œ ํ˜น์€ ์›๊ฒฉ ์‹œ์Šคํ…œ์˜ ์‘์šฉ์— ๊ฒฐํ•จ์„ ์ฃผ์ž…ํ•  ์ˆ˜ ์žˆ๋‹ค. ๊ฒฐํ•จ ์ฃผ์ž… ๋„๊ตฌ์— ๋Œ€ํ•œ ์‹คํ—˜์€ ODROID-XU4 ๋ณด๋“œ์—์„œ ์ง„ํ–‰ํ•˜์˜€๋‹ค.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 ์š” ์•ฝ 108Docto

    Self-Test Mechanisms for Automotive Multi-Processor System-on-Chips

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