FPGA-Based Reconfigurable Embedded Systems

Dear Colleagues,

Embedded systems are widely used across the entire world today, covering areas such as industrial controls, automotive electronics, medical electronics, consumer electronics, telecom/datacom, military/aerospace, etc. Reconfigurability is pushing embedded systems towards being more flexible, self-adaptive, and efficient. The customizable and programmable nature of FPGAs makes them an excellent alternative to ASICs as efficient hardware platforms for reconfigurable embedded systems. FPGAs provide opportunities for designers to quickly implement and evaluate different functions by reconfiguring the integrated computing logic and memory resources in the embedded systems.

However, FPGA-based reconfigurable embedded systems are very challenging because such systems, and especially the FPGAs, are typically constrained by limited computing, memory resources, bandwidth, power, and extreme environments. To tackle these problems, we need to refocus on the architecture, programming, implementation complexity, hardware and software co-design, etc., to determine the most efficient way to implement FPGA-based reconfigurable embedded systems. This Special Issue invites the submission of original contributions from both academic and industrial areas that focus on all topics related to FPGA-based reconfigurable embedded systems.

Topics

Topics of interests for this Special Issue include, but are not limited to, the following:

• Novel reconfigurable architectures, including overlay architectures for embedded systems with FPGAs.
• Resource-efficient/low-power/domain-specific design optimization for FPGA-based embedded systems.
• Co-design of hardware and software for FPGA-accelerated embedded systems.
• Abstractions, programming models, interfaces, and runtime management, including virtualization, for FPGA-based embedded systems.
• New languages and design frameworks for spatial or heterogeneous applications for FPGAs.
• System resilience/fault tolerance for embedded systems with FPGAs.
• Self-adaptive/AI embedded systems with FPGAs.
• Scheduling, management, and reconfiguration for real-time and/or networked embedded systems with FPGAs.
• Emerging technologies with in-field reconfiguration abilities for embedded systems.
• Industrial experience or case studies of FPGA-based reconfigurable embedded systems.

Dr. Zonghui Li
Dr. Yangdong Deng
Dr. Tao Li
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at mdpi.longhoe.net by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• embedded systems
• FPGAs
• reconfigurable architecture
• hardware and software co-design
• FPGA-accelerated embedded systems
• real-time/networked embedded systems
• AI/self-adaptive embedded systems