Embedded Multicore Processors and Systems

Levy, Markus; Conte, Thomas M.

doi:10.1109/mm.2009.41

Cited by 36 publications

(15 citation statements)

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“…Our experiments used direct and indirect approaches to search for temporal test vectors of a task running on an embedded multicore platform. There are a wide variety of applications of the QorIQ P4080 1 multicore processor (P4080) [17] in industrial real-time embedded systems [11], such as telecommunications and networking [18], and also on safety-critical systems, such as aerospace and defence markets [9]. The P4080 was used as the primary hardware platform in this study.…”

Section: Methodsmentioning

confidence: 99%

Dependent input sampling strategies

Srivisut

Clark

Paige

2018

Proceedings of the Genetic and Evolutionary Computation Conference

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Understanding extreme execution times is of great importance in gaining assurance in real-time embedded systems. The standard benchmark for dynamic testingÐuniform randomised testingÐis inadequate for reaching extreme execution times in these systems. Metaheuristics have been shown to be an efective means of directly searching for inputs with such behaviours but the increasing complexity of modern systems is now posing challenges to the efectiveness of this approach. The research reported in this paper investigates the use of metaheuristic search to discover biased random sampling regimes. Rather than search for test inputs, we search for distributions of test inputs that are then sampled. The search proceeds to discover and exploit relationships between test input variables, leading to sampling regimes where the distribution of a sampled parameter depends on the values of previously sampled input parameters. Our results show that test vectors indirectly generated from our dependent approach produce signiicantly more extreme (longer) execution times than those generated by direct metaheuristic searches. CCS CONCEPTS • Theory of computation → Optimization with randomized search heuristics; • Software and its engineering → Software testing and debugging; Search-based software engineering; • Computer systems organization → Multicore architectures;

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Section: Methodsmentioning

confidence: 99%

Dependent input sampling strategies

Srivisut

Clark

Paige

2018

Proceedings of the Genetic and Evolutionary Computation Conference

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“…A software-based implementation is required to efficiently manage such constantly evolving algorithms. Therefore, currently, commercial off-the-shelf multicore processors [5] are typically used in embedded systems for managing computationally heavy workloads that are subject to changes in the future.…”

Section: Introductionmentioning

confidence: 99%

Measurement-Based Power Optimization Technique for OpenCV on Heterogeneous Multicore Processor

2019

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Today’s embedded systems often operate computer-vision applications, and are associated with timing and power constraints. Since it is not simple to capture the symmetry between the application and the model, the model-based design approach is generally not applicable to the optimization of computer-vision applications. Thus, in this paper, we propose a measurement-based optimization technique for an open-source computer-vision application library, OpenCV, on top of a heterogeneous multicore processor. The proposed technique consists of two sub-systems: the optimization engine running on a separate host PC, and the measurement library running on the target board. The effectiveness of the proposed optimization technique has been verified in the case study of latency-power co-optimization by using two OpenCV applications—canny edge detection and squeezeNet. It has been shown that the proposed technique not only enables broader design space exploration, but also improves optimality.

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“…Though it is possible to deal with the heavy computational workloads by having specialized accelerators or coprocessors, it is not suitable to have such customized designs for embedded or cyber-physical systems in terms of economic feasibility or time-to-market. So, it is nowadays prevalent to use commercial-off-the-shelf multi-core processors [2] in embedded systems.…”

Section: Introductionmentioning

confidence: 99%

Efficiently Switchable Context-Aware Dataflow Adaptation Technique for Low-Power Multi-Core Embedded Systems

Jung

Yang

2019

IEEE Access

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Today's embedded systems operate under increasingly dynamic conditions. First, computational workloads can be either variable by nature or adjustable. Moreover, as many devices are batterypowered, it is common to have runtime power management technique, which results in dynamic power budget. This paper presents a design methodology for multi-core systems, based on dataflow specification, that can deal with various contexts. We optimize the original dataflow considering various working conditions, then, autonomously adapt it to a pre-defined optimal form in response to context changes. Such context changes at runtime might cause non-negligible delay or power budget violation. In order to overcome them, an efficient mode switching method is proposed. We show the effectiveness of the proposed technique with a real-life case study, stereo-vision, and synthetic benchmarks.INDEX TERMS Context-awareness, dataflow adaptation, low-power electronics, mode switching, multicore processing.

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Embedded Multicore Processors and Systems

Cited by 36 publications

References 1 publication

Dependent input sampling strategies

Dependent input sampling strategies

Measurement-Based Power Optimization Technique for OpenCV on Heterogeneous Multicore Processor

Efficiently Switchable Context-Aware Dataflow Adaptation Technique for Low-Power Multi-Core Embedded Systems

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