Dataflow Model–based Software Synthesis Framework for Parallel and Distributed Embedded Systems

2021 ◽  
Vol 26 (5) ◽  
pp. 1-38
Author(s):  
Eunjin Jeong ◽  
Dowhan Jeong ◽  
Soonhoi Ha
Keyword(s):  
Embedded Systems ◽  
Software Development ◽  
Synthesis Method ◽  
Real Life ◽  
Task Graph ◽  
Software Synthesis ◽  
Distributed Embedded Systems ◽  
Hardware Platform ◽  
Processing Elements ◽  
Model Based

Existing software development methodologies mostly assume that an application runs on a single device without concern about the non-functional requirements of an embedded system such as latency and resource consumption. Besides, embedded software is usually developed after the hardware platform is determined, since a non-negligible portion of the code depends on the hardware platform. In this article, we present a novel model-based software synthesis framework for parallel and distributed embedded systems. An application is specified as a set of tasks with the given rules for execution and communication. Having such rules enables us to perform static analysis to check some software errors at compile-time to reduce the verification difficulty. Platform-specific programs are synthesized automatically after the mapping of tasks onto processing elements is determined. The proposed framework is expandable to support new hardware platforms easily. The proposed communication code synthesis method is extensible and flexible to support various communication methods between devices. In addition, the fault-tolerant feature can be added by modifying the task graph automatically according to the selected fault-tolerance configurations by the user. The viability of the proposed software development methodology is evaluated with a real-life surveillance application that runs on six processing elements.

scholarly journals MODES: model-based optimization on distributed embedded systems

2021 ◽  
Author(s):  
Junjie Shi ◽  
Jiang Bian ◽  
Jakob Richter ◽  
Kuan-Hsun Chen ◽  
Jörg Rahnenführer ◽  
...  
Keyword(s):  
Machine Learning ◽  
Embedded Systems ◽  
Learning Model ◽  
Black Box ◽  
Distributed Embedded Systems ◽  
Data Set ◽  
Individual Model ◽  
Model Based ◽  
Machine Learning Model ◽  
Distributed Machine Learning

AbstractThe predictive performance of a machine learning model highly depends on the corresponding hyper-parameter setting. Hence, hyper-parameter tuning is often indispensable. Normally such tuning requires the dedicated machine learning model to be trained and evaluated on centralized data to obtain a performance estimate. However, in a distributed machine learning scenario, it is not always possible to collect all the data from all nodes due to privacy concerns or storage limitations. Moreover, if data has to be transferred through low bandwidth connections it reduces the time available for tuning. Model-Based Optimization (MBO) is one state-of-the-art method for tuning hyper-parameters but the application on distributed machine learning models or federated learning lacks research. This work proposes a framework $$\textit{MODES}$$ MODES that allows to deploy MBO on resource-constrained distributed embedded systems. Each node trains an individual model based on its local data. The goal is to optimize the combined prediction accuracy. The presented framework offers two optimization modes: (1) $$\textit{MODES}$$ MODES -B considers the whole ensemble as a single black box and optimizes the hyper-parameters of each individual model jointly, and (2) $$\textit{MODES}$$ MODES -I considers all models as clones of the same black box which allows it to efficiently parallelize the optimization in a distributed setting. We evaluate $$\textit{MODES}$$ MODES by conducting experiments on the optimization for the hyper-parameters of a random forest and a multi-layer perceptron. The experimental results demonstrate that, with an improvement in terms of mean accuracy ($$\textit{MODES}$$ MODES -B), run-time efficiency ($$\textit{MODES}$$ MODES -I), and statistical stability for both modes, $$\textit{MODES}$$ MODES outperforms the baseline, i.e., carry out tuning with MBO on each node individually with its local sub-data set.

Future Automotive Embedded Systems Enabled by Efficient Model-Based Software Development

2021 ◽  
Author(s):  
Juergen Schaefer ◽  
Herbert Christlbauer ◽  
Alexander Schreiber ◽  
Graham Reith ◽  
Mischa Jonker ◽  
...  
Keyword(s):  
Embedded Systems ◽  
Software Development ◽  
Model Based

scholarly journals COMPONENT-BASED EMBEDDED SOFTWARE ENGINEERING: DEVELOPMENT FRAMEWORK, QUALITY ASSURANCE AND A GENERIC ASSESSMENT ENVIRONMENT

2002 ◽  
Vol 12 (02) ◽  
pp. 107-133 ◽  
Author(s):  
XIA CAI ◽  
MICHAEL R. LYU ◽  
KAM-FAI WONG
Keyword(s):  
Quality Assurance ◽  
Embedded Systems ◽  
Software Development ◽  
Digital Signal Processor ◽  
Real Life ◽  
Digital Signal ◽  
Embedded Software ◽  
Development Framework ◽  
Assessment Environment ◽  
Flexible Component

Embedded software is used to control the functions of mechanical and physical devices by dedicated digital signal processor and computers. Nowadays, heterogeneous and collaborative embedded software systems are widely adopted to engage the physical world. To make such software extremely reliable, very efficient and highly flexible, component-based embedded software development can be employed for the complex embedded systems, especially those based on object-oriented (OO) approaches. In this paper, we introduce a component-based embedded software framework and the features it inherits. We propose a quality assurance (QA) model for component-based embedded software development, which covers both the component QA and the system QA as well as their interactions. Furthermore, we propose a generic quality assessment environment for component-based embedded systems: ComPARE. ComPARE can be used to assess real-life off-the-shelf components and to evaluate and validate the models selected for their evaluation. The overall component-based embedded systems can then be composed and analyzed seamlessly.

scholarly journals Hardware Software Co-Synthesis of Heterogenous Hypercube Architectures for Fault Tolerant Embedded Systems

2021 ◽  
Author(s):  
Jacob Levman
Keyword(s):  
Fault Tolerance ◽  
Embedded Systems ◽  
Fault Tolerant ◽  
Task Graph ◽  
Functional Requirements ◽  
System Specification ◽  
Synthesis Algorithm ◽  
Processing Elements ◽  
Software Modules ◽  
First Time

The hardware-software synthesis of an embedded system's architecture involves the partitioning of a system specification into hardware and software modules so as to meet various non-functional requirements. A designer can specify many non-functional requirements including cost, performance, reliability etc. In this thesis, we present an approach to the hardware-software co-synthesis of embedded systems targeting hypercube topologies. Hypercube topologies provide a flexible and reliable architecture for an embedded device with multiple processing elements. To the best of our knowledge, this is the first time that hypercube topologies have been supported in a co-synthesis algorithm. The co-synthesis approach represented here supports the following features: 1)input in the form of an acrylic periodic task graph with real-time constraints, 2) the pipelining of task graphs, 3) the use of a heterogeneous set of processing elements, 4) Support for fault tolerance through our newly developed group based fault tolerance technique. The co-synthesis algorithm has been applied to two case studies to demonstrate its efficacy.

Software Development of On-Board Power Electronics Equipment Using Model-Based Design Methodology

2014 ◽  
Vol 494-495 ◽  
pp. 1524-1528 ◽  
Author(s):  
Xiao Fei Liu ◽  
Shu Mei Cui ◽  
Wei Feng Gao ◽  
Shu Mei Cui ◽  
Shi Ming Xu
Keyword(s):  
Software Development ◽  
Power Electronics ◽  
Code Generation ◽  
Design Methodology ◽  
Model Building ◽  
Control Software ◽  
Hardware Platform ◽  
Model Based ◽  
Low Efficiency ◽  
Automatic Code

Model-Based Design (MBD) method is applied to power electronics device software development to overcome the problem of low efficiency in manual programming. The concept of Model-Based Design and several common development platforms are introduced. Based on tools in Simulink, an on-board charger control software is developed. Meanwhile the hardware platform, the model building, the model validation and the automatic code generation are also described. Experiments are carried out in the hardware platform to verify the correctness and feasibility of the codes.They are helpful for the software development of power electronics equipments.

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