Intelligent Embedded Software: New Perspectives and Challenges

Intelligent embedded systems (IES) represent a novel and promising generation of embedded systems (ES). IES have the capacity of reasoning about their external environments and adapt their behavior accordingly. Such systems are situated in the intersection of two different branches that are the embedded computing and the intelligent computing. On the other hand, intelligent embedded software (IESo) is becoming a large part of the engineering cost of intelligent embedded systems. IESo can include some artificial intelligence (AI)-based systems such as expert systems, neural networks and other sophisticated artificial intelligence (AI) models to guarantee some important characteristics such as self-learning, self-optimizing and self-repairing. Despite the widespread of such systems, some design challenging issues are arising. Designing a resource-constrained software and at the same time intelligent is not a trivial task especially in a real-time context. To deal with this dilemma, embedded system researchers have profited from the progress in semiconductor technology to develop specific hardware to support well AI models and render the integration of AI with the embedded world a reality

Teaching HW/SW codesign with a Zynq ARM/FPGA SoC

© 2017 IEEE. In this paper we describe a lab session-based hardware/software (HW/SW) codesign course for implementing embedded systems. The goals of the course are to teach the fundamental concepts of embedded system design, develop hands-on HW/SW codesign skills, and to show that there are many possible ways to explore the design space. The reason behind choosing HW/SW codesign approach is that it brings the best of the two worlds: the flexibility of SW and the power/energy/computation efficiency of HW. As an example project, students codesign the well-known RSA public-key cryptosystem in the Xilinx Zybo boards that contain a Xilinx 7-series FPGA coupled with an embedded ARM processing unit. Students are required to explore the design space, weigh the various alternatives and take design decisions. Besides, the project cultivates non-technical skills such as team building and management, sharing of work-load, decision making, presentation and technical report writing

Hardware/software codesign of configurable fuzzy control systems

Fuzzy inference techniques are an attractive and well-established approach for solving control problems. This is mainly due to their inherent ability to obtain robust, low-cost controllers from the intuitive (and usually ambiguous or incomplete) linguistic rules used by human operators when describing the control process. This paper focuses on the hardware/software codesign of configurable fuzzy control systems. Two prototype systems implemented on general-purpose development boards are presented. In both of them, hardware components are based on specific and configurable fuzzy inference architecture whereas software tasks are supported by a microcontroller. The first prototype uses an off-the-shelf microcontroller and a low-complexity Xilinx XC4005XL field programmable gate array (FPGA). The second one is implemented as a system on programmable chip (SoPC), integrating the microcontroller together with the fuzzy hardware architecture and its interface circuits into a Xilinx Spartan2E200 FPGA.Comisión Interministerial de Ciencia y Tecnología TIC2001-1726-C02-0

Codesign for People with Aphasia Through Tangible Design Languages

Codesign techniques encourage designers and end-users to work together in the creation of design solutions, but often make assumptions about the ways in which participants will be able to communicate. This can lead to the unwitting exclusion of people with communication impairments from the design of technologies that have the potential to transform their lives. This paper reports our research into codesign techniques for people whose communication skills are impaired. A variety of techniques were explored on two projects; some were adaptations of existing codesign techniques, others were created specially. In both cases, the emphasis was on creating tangible design languages. The results illustrate how people with communication impairments can be given a voice in design and demonstrate the benefits of doing so

Hardware-software codesign in a high-level synthesis environment

Interfacing hardware-oriented high-level synthesis to software development is a computationally hard problem for which no general solution exists. Under special conditions, the hardware-software codesign (system-level synthesis) problem may be analyzed with traditional tools and efficient heuristics. This dissertation introduces a new alternative to the currently used heuristic methods. The new approach combines the results of top-down hardware development with existing basic hardware units (bottom-up libraries) and compiler generation tools. The optimization goal is to maximize operating frequency or minimize cost with reasonable tradeoffs in other properties. The dissertation research provides a unified approach to hardware-software codesign. The improvements over previously existing design methodologies are presented in the frame-work of an academic CAD environment (PIPE). This CAD environment implements a sufficient subset of functions of commercial microelectronics CAD packages. The results may be generalized for other general-purpose algorithms or environments. Reference benchmarks are used to validate the new approach. Most of the well-known benchmarks are based on discrete-time numerical simulations, digital filtering applications, and cryptography (an emerging field in benchmarking). As there is a need for high-performance applications, an additional requirement for this dissertation is to investigate pipelined hardware-software systems\u27 performance and design methods. The results demonstrate that the quality of existing heuristics does not change in the enhanced, hardware-software environment

An FPGA Kalman-MPPT implementation adapted in SST-based dual active bridge converters for DC microgrids systems

The design of digital hardware controllers for the integration of renewable energy sources in DC microgrids is a research topic of interest. In this paper, a Kalman filter-based maximum power point tracking algorithm is implemented in an FPGA and adapted in a dual active bridge (DAB) converter topology for DC microgrids. This approach uses the Hardware/Software (HW/SW) co-design paradigm in combination with a pipelined piecewise polynomial approximation design of the Kalman-maximum power point tracking (MPPT) algorithm instead of traditional lookup table (LUT)-based methods. Experimental results reveal a good integration of the Kalman-MPPT design with the DAB-based converter, particularly during irradiation and temperature variations due to changes in weather conditions, as well as a good balanced hardware design in complexity and area-time performance compared to other state-of-art FPGA designs