McGill downtown campus quad, facing Redpath Museum.

Photo by Negin Firouzian

Reliable Silicon Systems Lab

Department of Electrical and Computer Engineering, McGill University

The Reliabile Silicon Systems Lab (RSSL), in the Department of Electrical and Computer Engineering at McGill University, conducts computer system optimization research targeting a wide variety of applications, from safety-critical automotive and aerospace systems, to machine learning on complex multiprocessors.

Computer system design faces a multitude of challenges today, given the expectations of reliable high performance software, and low-power execution, on affordable hardware. RSSL is dedicated to the development of novel architectures and automation methodologies that support hardware-software co-design and optimization of heterogeneous multiprocessor systems. Recent topics include research on:

  • Computer architecture and automated computer system design
  • Fault-tolerant and safety-critical system design
  • Aerospace and automative system security
  • Hardware-software optimization of machine learning systems

RSSL is directed by Professor Brett H. Meyer, who has more than 15 years of experience in research on the optimization of computer systems; the lab is supported by funding from the Natural Sciences and Engineering Research Council of Canada (NSERC), the Fonds de recherche du Québec (FRQNT), and, industrial sponsors.

Interested in joining the team? Learn about out what we’re currently looking for in new members.

Quickly browse our past publications here:

News - Page 2 of 2

Poster: Optimizing Keyword Spotting on Microcontrollers

Undergraduate Adithya Lakshminarayanan presented his summer research at the SURE Poster Session today. It explores the different trade-offs inherent in quantizing models for keyword spotting. FP is best for top accuracy, but 8- and 16-bit models each strike interesting trade-offs under tighter constraints.

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New website!

Please bear with us as we move our website to Jekyll and slowly add content.

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