Hardware and Software Co-Design in Intelligent Systems
A special issue of Electronics (ISSN 2079-9292).
Deadline for manuscript submissions: 15 February 2026 | Viewed by 28
Special Issue Editors
Interests: hardware-software co-design; very large scale integration (VLSI) design; hardware security; integrated circuit reliability
Special Issue Information
Dear Colleagues,
We are seeking high-quality research papers for the Special Issue "Hardware and Software Co-design in Intelligent Systems".
The rapid advancement of artificial intelligence (AI) is reshaping scientific and industrial domains, driving the development of increasingly sophisticated intelligent systems. As the complexity of AI models grows, hardware-software (HW/SW) co-design has become essential to the creation of efficient, high-performance intelligent systems. AI algorithms must be optimized to suit specific platforms, and domain-specific hardware accelerators should be implemented to ensure the efficient execution of AI workloads. By seamlessly integrating hardware and software, co-design facilitates the effective deployment of AI across a broad range of applications, supporting both cloud and edge computing paradigms.
While HW/SW co-design offers significant advantages, it faces several limitations, such as compatibility issues, significant constraints—especially on edge devices—the need for continuous adaptation to evolving AI models, and a lack of standardization. To tackle these challenges, we are seeking submissions of original research articles and reviews from both academic and industrial experts in the field of HW/SW co-design for AI.
Potential topics include (but are not limited to):
- Algorithms: Advanced AI and compression techniques, including pruning, quantization, and distillation, to enable low-cost, low-footprint deployment;
- Hardware: Domain-specific architectures and implementations for machine learning (ML), including digital and analog circuits, FPGAs, SoCs, MCUs, and both in-memory and near-memory architectures;
- Software: Compilers optimized for efficient ML execution; integrated environments for end-to-end AI development; embedded software and embedded AI solutions, as well as ML operations (MLOps) for streamlined model management;
- Systems: Distributed ML systems; heterogeneous AI systems involving CPUs, GPUs, FPGAs, and domain-specific accelerators; edge AI systems;
- Applications: Application-specific ML deployment tailored to industry needs and use cases;
- Benchmarking and Evaluation: Performance benchmarking and evaluation for ML platforms.
Dr. Shengyu Duan
Dr. Chenhong Cao
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com 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.
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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.
Keywords
- hardware-software co-design
- artificial intelligent system
- machine learning
- model compression
- domain-specific architecture
- end-to-end framework
- heterogeneous AI
- edge AI ML benchmark
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