Academic literature on the topic 'Heterogeneous embedded system'

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Journal articles on the topic "Heterogeneous embedded system"

1

Valente, Giacomo, Tiziana Fanni, Carlo Sau, Tania Di Mascio, Luigi Pomante, and Francesca Palumbo. "A Composable Monitoring System for Heterogeneous Embedded Platforms." ACM Transactions on Embedded Computing Systems 20, no. 5 (2021): 1–34. http://dx.doi.org/10.1145/3461647.

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Advanced computations on embedded devices are nowadays a must in any application field. Often, to cope with such a need, embedded systems designers leverage on complex heterogeneous reconfigurable platforms that offer high performance, thanks to the possibility of specializing/customizing some computing elements on board, and are usually flexible enough to be optimized at runtime. In this context, monitoring the system has gained increasing interest. Ideally, monitoring systems should be non-intrusive, serve several purposes, and provide aggregated information about the behavior of the different system components. However, current literature is not close to such ideality: For example, existing monitoring systems lack in being applicable to modern heterogeneous platforms. This work presents a hardware monitoring system that is intended to be minimally invasive on system performance and resources, composable, and capable of providing to the user homogeneous observability and transparent access to the different components of a heterogeneous computing platform, so system metrics can be easily computed from the aggregation of the collected information. Building on a previous work, this article is primarily focused on the extension of an existing hardware monitoring system to cover also specialized coprocessing units, and the assessment is done on a Xilinx FPGA-based System on Programmable Chip. Different explorations are presented to explain the level of customizability of the proposed hardware monitoring system, the tradeoffs available to the user, and the benefits with respect to standard de facto monitoring support made available by the targeted FPGA vendor.
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2

Jammalamadaka, Sastry Kodanda Rama, Valluru Sai Kumar Reddy, and Smt J Sasi Bhanu. "Networking Heterogeneous Microcontroller based Systems through Universal Serial Bus." International Journal of Electrical and Computer Engineering (IJECE) 5, no. 5 (2015): 992. http://dx.doi.org/10.11591/ijece.v5i5.pp992-1002.

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Networking heterogeneous embedded systems is a challenge. Every distributed embedded systems requires that the network is designed specifically considering the heterogeneity that exits among different Microcontroller based systems that are used in developing a distributed embedded system. Communication architecture, which considers the addressing of the individual systems, arbitration, synchronisation, error detection and control etc., needs to be designed considering a specific application. The issue of configuring the slaves has to be addressed. It is also important that the messages, flow of the messages across the individual ES systems must be designed. Every distributed embedded system is different and needs to be dealt with separately. This paper presents an approach that addresses various issues related to networking distributed embedded systems through use of universal serial bus communication protocol (USB). The approach has been applied to design a distributed embedded that monitors and controls temperatures within a Nuclear reactor system.
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3

Zhang, Huafeng, Hehua Zhang, Ming Gu, and Jiaguang Sun. "Modeling a Heterogeneous Embedded System in Coloured Petri Nets." Journal of Applied Mathematics 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/943094.

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Embedded devices are everywhere now and, unlike personal computers, their systems differ in implementation languages and behaviors. Interactions of different devices require programmers to master programming paradigms in all related languages. So, a defect may occur if differences in systems' behaviors are ignored. In this paper, a heterogeneous system which is composed of two subsystems is introduced and we point out a potential defect in this system caused by an interface mismatch. Then, a state based approach is applied to verify our analysis of the system.
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4

Syschikov, Alexey, Yuriy Sheynin, Boris Sedov, and Vera Ivanova. "Domain-Specific Programming Environment for Heterogeneous Multicore Embedded Systems." International Journal of Embedded and Real-Time Communication Systems 5, no. 4 (2014): 1–23. http://dx.doi.org/10.4018/ijertcs.2014100101.

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Nowadays embedded systems are used in a broad range of domains such as avionics, space, automotive, mobile, domestic appliances etc. Sophisticated software determines the quality of embedded systems and requires high-qualified experts for software development. Software becomes the main assert of embedded systems that is valuable to retain in changing computing platforms in embedded systems evolution. Computing platforms for embedded systems became multicore processors and SoC, they can change in the embedded system lifetime that could be long (dozen of years for an automobile and airplane). It requires software porting to new platforms as a regular process. Many tools and approaches allow developing of software for domain area experts, but mainly for general-purpose computing systems. In this paper the authors present the complex technology and tools that allows involving domain experts in software development for embedded systems. The proposed technology has various aspects and abilities that can be used to build verifiable and portable software for a wide range of embedded platforms.
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5

Wu, Dian Hong. "Task Optimization Scheduling Algorithm in Embedded System Based on Internet of Things." Applied Mechanics and Materials 513-517 (February 2014): 2398–402. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.2398.

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Embedded system has been widely used in the network, server, etc., and it has a good application prospect with the development of Internet of things. In the embedded heterogeneous computing system, task scheduling is the key to deciding the system performance. For multi-task scheduling, the current scheduling algorithm is mostly based on task duplication, without a full consideration of the correlation between the predecessor task and its subsequent tasks. Based on modeling the multi-frame task scheduling problem in the heterogeneous embedded system, this paper analyzes the availability of tasks through the design of genetic algorithm, so as to verify the algorithm's feasibility, which is of important guiding significance for the multi-task scheduling in the embedded heterogeneous computing system.
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6

Pervan, Branimir, Josip Knezović, and Emanuel Guberović. "Energy-efficient distributed password hash computation on heterogeneous embedded system." Automatika 63, no. 3 (2022): 399–417. http://dx.doi.org/10.1080/00051144.2022.2042115.

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7

Rath, A. K., and S. N. Dehuri. "Non-dominated Sorting Genetic Algorithms for Heterogeneous Embedded System Design." Journal of Computer Science 2, no. 3 (2006): 288–91. http://dx.doi.org/10.3844/jcssp.2006.288.291.

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8

E, Mounika. "A Hybridised Heterogeneous Embedded System Networking through Multi-Master Interface." International Journal of Emerging Trends in Engineering Research 8, no. 3 (2020): 885–93. http://dx.doi.org/10.30534/ijeter/2020/45832020.

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9

Majumdar, Abhinandan, Srihari Cadambi, and Srimat T. Chakradhar. "An Energy-Efficient Heterogeneous System for Embedded Learning and Classification." IEEE Embedded Systems Letters 3, no. 1 (2011): 42–45. http://dx.doi.org/10.1109/les.2010.2100802.

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10

Campeanu, Gabriel, and Mehrdad Saadatmand. "A Two-Layer Component-Based Allocation for Embedded Systems with GPUs." Designs 3, no. 1 (2019): 6. http://dx.doi.org/10.3390/designs3010006.

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Component-based development is a software engineering paradigm that can facilitate the construction of embedded systems and tackle its complexities. The modern embedded systems have more and more demanding requirements. One way to cope with such a versatile and growing set of requirements is to employ heterogeneous processing power, i.e., CPU–GPU architectures. The new CPU–GPU embedded boards deliver an increased performance but also introduce additional complexity and challenges. In this work, we address the component-to-hardware allocation for CPU–GPU embedded systems. The allocation for such systems is much complex due to the increased amount of GPU-related information. For example, while in traditional embedded systems the allocation mechanism may consider only the CPU memory usage of components to find an appropriate allocation scheme, in heterogeneous systems, the GPU memory usage needs also to be taken into account in the allocation process. This paper aims at decreasing the component-to-hardware allocation complexity by introducing a two-layer component-based architecture for heterogeneous embedded systems. The detailed CPU–GPU information of the system is abstracted at a high-layer by compacting connected components into single units that behave as regular components. The allocator, based on the compacted information received from the high-level layer, computes, with a decreased complexity, feasible allocation schemes. In the last part of the paper, the two-layer allocation method is evaluated using an existing embedded system demonstrator; namely, an underwater robot.
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