Overview of Ai at the Edge FPGAs
This workshop will focus on deploying AI models on FPGA boards. ML on chip or AI at the Edge is an emerging field and skilled people in this domain are highly sought-after in the tech industry. Join us for this 5 day intensive workshop to develop this high in-demand skill.
WHY AI AT THE EDGE
Quantized training & implementation of NNs (major)
Edge device landscape – Holistic Overview
Why FPGAs are suitable as accelerators for Neural Networks?
Quantized training and implementation of NNs
Real-time inference concepts
Hands on experience with Xilinx development tools
Topics of the Workshop include, but are not limited to
– Introduction to Machine and Deep Learning
– Overview of AI at the Edge/ML on Chip
– Vivado HLS basics
– Breivats implementation
We Will Provide
All resource materials used in the commencement of this workshop will be provided to the participants.
Pre Requisites for the Workshop Participants
- Python – pytorch
- Basic understanding of Deep learning models
- Basic background in computer architecture like pipelining, caching, instruction-set, assembly programming (for advanced workshops on FPGAs)
- Basic understanding of C/C++
- Basic understanding of Xilinx FPGAs (optional)
Assistant Professor, SEECS-NUST
Dr. Abid Rafique
Dr. Abid has 19 years of experience in leading teams in public R&D organization on signal processing algorithms, design of FPGA-based high performance computing platforms and hardware acceleration of critical algorithms. He has co-founded multiple startups including Untangle Solutions, Galaxonic and AuditXPRT Technologies with recent exit from AuditXPRT worth 6M GBP. He has a unique skill set of building meaningful business relationships and high performance teams. He holds an MS in Embedded Systems from TU Munich, Germany and a PhD in High Performance Reconfigurable Computing from Imperial College London,UK.
Dr. Muhammad Adeel Pasha from SBASSE, LUMS, Lahore. Dr. Adeel Pasha works in the area of low-power microarchitecture, energy-efficient hardware design, hardware acceleration of machine learning and deep neural networks, and green computing. He is an Associate Professor at the EE Department, LUMS where he is also serving as the Director of Electronics and Embedded Systems Lab (EESL) since 2014. He is also contributing to the NECOP Fellowship program on Digital IC Design being hosted at LUMS.
Dr. Hassan Aqeel Khan has a PhD in Electrical Engineering from Michigan State University, USA. He is currently working as an Assistant Professor in the Kingdom of Saudi Arabia. He worked as an Assistant Professor at NUST SEECS, Islamabad, Pakistan from November 2015 to December 2019. He has multiple years of teaching and research experience in AI and Machine Learning and a number of his former students are now working as Data Scientists and AI professionals or pursuing graduate studies at leading international Universities. Dr. Khan’s research is primarily focused on Medical Imaging and Biomedical Engineering applications of AI and Computer Vision. He is a founding member of AI Lounge.
WHY AI AT THE EDGE
Verified Certificates will be provided by AI Lounge to all the workshop participants.
The duration of this workshop will be five consecutive days, with eight hour session each day.
Jan 24th –
Workshop on Campus
Workshop will be conducted in NICHE – NUST.
Earlybird Registration Now Open
Professionals get 20% Discount till 10th Jan 2022