Proposal procedure
Special session proposals shall be sent to norcas@tuni.fi by June 15, 2023. Accepted special sessions will be added to the paper submission system and the conference web site once approved by the organizers.
To propose a Special Session, send the proposed session title/topic, organizer(s) name, affiliation and email, a short paragraph on the rationale of the session, and the names and email addresses of five proposed (PhD level) reviewers for the papers submitted to the session. The session organizer commits to chair the session in the conference if the session will be accepted.
1-2 of each special session organizers will be offered a reduced rate to participate (with the disclaimer that for each paper presented in the conference there must be one paid full registration).
Accepted Special Sessions
Digital Design and Verification with Chisel
Organizers: Martin Schoeberl, DTU and Hans Jakob Damsgaard, Tampere University
The performance growth of general-purpose processor cores is coming to a halt as we approach the end of Moore’s law and Dennard scaling. As a result, meeting the compute and energy efficiency requirements of future applications requires the use of domain-specific accelerators. However, traditional tools and languages used for designing such architectures are cumbersome to work with, causing impractical, long development cycles.
In response, recent research has proven that hardware designers can learn from software development practices to efficiently build and verify accelerators. Novel languages like Chisel are at the heart of this research and provide new features for hardware construction and verification to designers. This special session’s interest lies in, but is not limited to digital design with Chisel, hardware generators, extensions of the Chisel language or its compiler backend, Chisel-based libraries, formal or simulation-based verification with Chisel, and Chisel in teaching. Submissions founded in other hardware construction languages are also welcomed.
Materials and Devices for Future Circuits and Systems
Organizer: Ming Shen, Aalborg University
The key objective of this session is to create a platform for experts, scholars, and industry professionals from various sectors to discuss recent advancements, challenges, and future trends in the field of material science and its integration into the next generation of information devices and systems. The topics include but not limited to:
- Spin Wave Devices for Novel Information Systems
- Magnetic Nano material and Nano Robots
- Magnetoelectric / Multiferroic Devices
- Barium Strontium Titanate (BST) Thin Films
- Nonreciprocal and Switchable Devices
- Silicon-Micromachined THz Systems
Approximate Computing circuits and systems
Organizers: Jari Nurmi, Tampere University and Anil Kanduri, University of Turku
Performance, implementation complexity and energy consumption have been the key optimization parameters for digital circuits and systems already for decades. Regarding energy, it is made up from the power consumption and computation time (E = P x t), where the time represents performance, and both the power and time are also dependent on the implementation complexity. There is an inherent trade-off between these optimization criteria, which is hard to break to bring the energy consumption down considerably. However, by introducing a new dimension, accuracy, to the design optimization, significant reductions in the computation complexity, power and time and thus lower energy can be achieved. The energy efficiency can even be improved by a factor of 10x-50x in the most prominent cases, which is far beyond what can be reached when sticking to the conventional and conservative best available accuracy.
There are several application areas where reducing the accuracy either end-to-end or locally is tolerable, e.g., machine learning, data mining, sensor signal processing, and audiovisual human-perceived signals. The accuracy reduction can be permanent or adjustable at run-time. Resource constrained devices such IoT and edge processors have benefitted from the energy efficiency by exploiting the accuracy trade-offs. Opportunities for approximation span vertically across the computing stack ranging from algorithms down to low level hardware. Cross layer interaction and awareness is one of the key areas for disciplined tuning of approximation to maximize the performance and energy gains while ensuring accuracy guarantees.
For this special session, we are looking for Approximate Computing solutions in the following areas (but not strictly limited to):
- Approximate memory techniques
- Approximating logic implementations
- Arithmetics and number systems supporting multiple precisions
- Approximate algorithms and software
- Error resilience techniques allowing for approximation
- Analog approximations of digital functionalities
- Adaptive approximation approaches
- Systems and applications exploiting approximate computing
- Application/domain specific optimizations
Circuits and Systems in AI and Neuromorphic Computing
Organizers: to be announced…