DescriptionCMC Microsystems is pleased to organize the third workshop on accelerating AI, highlighting the challenges and opportunities of AI acceleration from the cloud to the edge. This workshop aims to bring together experts from industry and academia to share their latest achievements and innovations in the field of AI and machine learning algorithms, software, and hardware from the cloud to deeply embedded machine learning systems.
- ML applications: Computer Vision, NLP, EDA and CAD…
- Novel AI HW: GPUs, FPGAs and Custom Accelerators
- Software stack: libraries, compilers, and ML frameworks
- ML Benchmarking on Emerging Hardware
- AI Latest trends in chip design and commercialization.
This workshop will
- Promote innovation, adoption and early access to advanced technologies including silicon and systems for accelerating AI workloads from cloud to the edge.
- Share insights and experiences with others; explore collaboration opportunities and connect leaders from industry to AI researchers and start-ups.
- Influence technology selection (roadmap) and development activities of emerging AI trends.
Target AttendeesThe workshop is open to professors, research associates and graduate students at Canadian universities as well as industrial attendees who wish to provide input and advice.
|May 4, 2022||1:00 pm to 5:00 pm EDT||Virtual|
|1:00 – 1:05||Yassine Hariri||CMC Microsystems||Welcome and opening remarks|
|1:05 – 1:25||Qian Wang||Huawei Technologies Canada||CANN: Unified Heterogeneous Computing Architecture to Unleash Ultimate Hardware Computing Power|
|1:25 – 1:45||Warren Gross||McGill University||Edge Intelligence|
|1:45 – 2:05||Davis Sawyer||Deeplite||Deeplite Runtime (DeepliteRT): Ultra-Compact Quantization for AI on Arm CPUs|
|2:05 – 2:25||Miodrag Bolic||University of Ottawa||Computer Architectures and Algorithms: From Filtering to Deep Learning|
|2:25 – 2:45||Andreas Moshovos||University of Toronto||Machine Learning Anywhere/Anytime: Purpose-Built Computing Hardware|
|2:45 – 2:50||Break|
|2:50 – 3:10||Griffin Lacey||Nvidia||Improving GPU Utilization with Multi-Instance GPU (MIG)|
|3:10 – 3:30||Rick O’Connor||OpenHW Group||CORE-V Cores: industrial grade, open-source RISC-V cores enabling AI accelerators at the edge|
|3:30 – 3:50||Dusan Gostimirovic||McGill University||Deep Learning for the Prediction and Correction of Fabrication Errors in Fine-Featured Silicon Photonics Circuits|
|3:50 – 4:10||Nizar El Zarif||Polytechnique Montréal||Extending and implementing RISC V vector instructions for accelerating AI workload|
|4:10 – 4:30||George Shaker||University of Waterloo||TBD|
|4:30 – 5:00||Open Discussion|
Pricing and Registration
Yassine Hariri, Hariri@cmc.ca, CMC Microsystems
Over 15 years of experience in advanced computing systems from the cloud to the very edge, with a focus on artificial intelligence, computer vision, video, image and sensor fusion workloads acceleration, FPGA based prototyping, software stack, and domain-specific hardware architectures. Currently leading projects related to the specification, development, implementation, deployment, and support of the next generation of advanced computing infrastructure mainly FPGAs, GPUs, and Custom Hardware for AI applications. Dr. Hariri earned his B.A.Sc. in Computer Engineering from Ecole Marocaine des Sciences de l’ingénieur, Casablanca, Morocco, in 1998, and the M.S. and Ph.D. degrees from Ecole de Technologie Supérieure (ETS), Montreal, QC, Canada, in 2002 and 2008, respectively, all in electrical engineering.
If you have any comments or questions regarding the contents of this workshop, please contact Dr. Yassine Hariri at Hariri@cmc.ca.
Course cancellations must be received in writing at least one (1) week before the beginning date of the course in question to receive a full refund of the registration fee. A cancellation made after the deadline will not receive a refund. CMC Microsystems makes no commitments on refunds for travel or accommodations.