The 36th IEEE Workshop on Signal Processing Systems

SiPS 2022


Computing Systems



IEEE SiPS 2022
The 36th IEEE Workshop on Signal Processing Systems
November 2-4, 2022, Rennes, France
Supported by IEEE CAS (Circuit and Systems Society) and IEEE SPS (Signal Processing Society)
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SiPS 2022 website: http://sips2022.insa-rennes.fr
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The IEEE Workshop on Signal Processing Systems (SiPS) is a premier international forum in the
area of design and implementation of signal processing systems. It addresses all aspects of
architecture and design methods of these systems. Emphasis is on current and future
challenges in research and development in both academia and industry.
IEEE SiPS 2022 is the 36th edition of this annual conference supported by
IEEE CAS (Circuit and Systems Society) and IEEE SPS (Signal Processing Society).
The program for the 2022 edition includes a demo night session of demonstrations and posters,
as well as two special sessions on system cybersecurity and signal processing systems
for space and astronomy applications.
The social event is organized at Mont Saint Michel, a site inscribed on the UNESCO list of
World Heritage Sites, and the theme of the year for the 2022 edition is sustainable systems.
Two submission formats are proposed: a "Journal Track" published directly in Springer
Journal of Signal Processing Systems (JSPS) and a "Conference Track" published in
IEEE Explore. The deadline for submission of manuscripts is April 15, 2022.
More information on http://sips2022.insa-rennes.fr.
TOPICS OF INTEREST
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We invite prospective authors to submit original papers either to the 6-page conference track
or to the 12-page journal track in areas including, but not limited to:
Theme of the Year: Towards Sustainable Systems
- Low energy systems
- Low environmental impact systems
Software Implementation of Signal Processing Systems
- Software on programmable digital signal processors
- Application-specific instruction-set processor (ASIP) architectures and systems
- SIMD, VLIW and multi-core CPU architectures
- GPU-based massively parallel implementations
Hardware Implementation of Signal Processing Systems
- Low-power signal processing circuits and applications
- High-performance VLSI systems
- FPGA and reconfigurable architecture-based systems
- System-on-chip and network-on-chip
- VLSI for sensor network and RF identification systems
- Processing-in-memory signal processing systems
Machine Learning for Signal Processing
- Circuits and systems for AI
- Deep learning/machine learning/AI algorithms
- Tools/platforms for AI
- Edge and cloud AI computing platforms
- Hardware/neuromorphic accelerators
- Hardware/software co-design and automation for AI
Design Methods of Signal Processing Systems
- Optimization of signal processing algorithms
- Compilers and tools for signal processing systems
- Algorithm-to-architecture transformation
- Dataflow-based design methodologies
- Error-tolerant techniques for signal processing
Signal Processing Application Systems
- Audio, speech, and language processing
- Biomedical signal processing and bioinformatics
- Image, video, and multimedia signal processing
- Information forensics, security, and cryptography
- Sensing and sensor signal processing
- Signal processing for non-volatile memory systems
- Latency-and power-constrained signal processing
- Wireless communications and MIMO systems
- Coding and compression
- Signal processing for mixed-signal technologies
IMPORTANT DATES
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Technical Papers: April 15, 2022
Special Session Proposals: April 15, 2022
COMMITTEE
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General Chairs
John McAllister, QUB
Maxime Pelcat, INSA Rennes, IETR
Program Chairs
Francesca Palumbo, UNISS
Daniel Menard, INSA Rennes, IETR
Publication Chair
Raquel Lazcano, UNISS
Communication Chairs
Herve Yviquel, UNICAMP
Xiaodong Yu, ANL
Finance Chair
Jean-Francois Nezan, INSA Rennes, IETR
Special Sessions Chair
Philippe Coussy, LabSTICC
Local Organization Chair
Karol Desnos, INSA Rennes, IETR
Asian Liaison: Gwo Giun Lee, NCKU
European Liaison: Eduardo Juarez Martinez, UPM
North American Liaison: Shuvra S. Bhattacharyya, UMD