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      An Overview of the nMPRA and nHSE Microarchitectures for Real-Time Applications

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          Abstract

          In the context of real-time control systems, it has become possible to obtain temporal resolutions of microseconds due to the development of embedded systems and the Internet of Things (IoT), the optimization of the use of processor hardware, and the improvement of architectures and real-time operating systems (RTOSs). All of these factors, together with current technological developments, have led to efficient central processing unit (CPU) time usage, guaranteeing both the predictability of thread execution and the satisfaction of the timing constraints required by real-time systems (RTSs). This is mainly due to time sharing in embedded RTSs and the pseudo-parallel execution of tasks in single-processor and multi-processor systems. The non-deterministic behavior triggered by asynchronous external interrupts and events in general is due to the fact that, for most commercial RTOSs, the execution of the same instruction ends in a variable number of cycles, primarily due to hazards. The software implementation of RTOS-specific mechanisms may lead to significant delays that can affect deadline requirements for some RTSs. The main objective of this paper was the design and deployment of innovative solutions to improve the performance of RTOSs by implementing their functions in hardware. The obtained architectures are intended to provide feasible scheduling, even if the total CPU utilization is close to the maximum limit. The contributions made by the authors will be followed by the validation of a high-performing microarchitecture, which is expected to allow a thread context switching time and event response time of only one clock cycle each. The main purpose of the research presented in this paper is to improve these factors of RTSs, as well as the implementation of the hardware structure used for the static and dynamic scheduling of tasks, for RTOS mechanisms specific to resource sharing and intertask communication.

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          Predictable programming on a precision timed architecture

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            Scalable ESPRIT Processor for Direction-of-Arrival Estimation of Frequency Modulated Continuous Wave Radar

            The estimation of signal parameters via rotational invariance techniques (ESPRIT) is an algorithm that uses the shift-invariant properties of the array antenna to estimate the direction-of-arrival (DOA) of signals received in the array antenna. Since the ESPRIT algorithm requires high-complexity operations such as covariance matrix and eigenvalue decomposition, a hardware processor must be implemented such that the DOA is estimated in real time. Additionally, the ESPRIT processor should support a scalable number of antenna configuration for DOA estimation in various applications because the performance of ESPRIT depends on the number of antennas. Therefore, we propose an ESPRIT processor that supports two to eight scalable antenna configuration. In addition, since the proposed ESPRIT processor is based on multiple invariances (MI) algorithm, it can achieve a much better performance than the existing ESPRIT processor. The execution time is reduced by simplifying the Jacobi method, which has the most significant computational complexity for calculating eigenvalue decomposition (EVD) in ESPRIT. Moreover, the ESPRIT processor was designed using hardware description language (HDL), and an FPGA-based verification was performed. The proposed ESPRIT processor was implemented with 10,088 slice registers, 18,207 LUTs, and 80 DSPs, and the slice register, LUT, and DSP were reduced by up to 71.45%, 54.5%, and 68.38%, respectively, compared to the existing structure.
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              Hardware RTOS: Custom Scheduler Implementation Based on Multiple Pipeline Registers and MIPS32 Architecture

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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                30 June 2021
                July 2021
                : 21
                : 13
                : 4500
                Affiliations
                [1 ]Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University, 720229 Suceava, Romania
                [2 ]Integrated Center for Research, Development and Innovation in Advanced Materials, Nanotechnologies, and Distributed Systems for Fabrication and Control (MANSiD), Stefan cel Mare University, 720229 Suceava, Romania
                Author notes
                [* ]Correspondence: vgaitan@ 123456usm.ro (V.G.G.); zagan@ 123456usm.ro (I.Z.)
                Author information
                https://orcid.org/0000-0003-1322-4516
                Article
                sensors-21-04500
                10.3390/s21134500
                8271378
                34209323
                ab18d78d-6da9-41ca-99f6-5ea52f528ba1
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 05 June 2021
                : 28 June 2021
                Categories
                Article

                Biomedical engineering
                nmpra architecture,hardware rtos,rapid reaction to stimuli,fast context switch,resource multiplication

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