Configure Your Research Platform

- Infrastructure Needs for Implementing Machine Learning on Heterogeneous Computing Systems

at 2:00 pm

There is an increasing need in accelerating compute intensive machine learning workloads targeting heterogeneous computing systems.

A variety of accelerators ranging from high-end desktop GPUs, FPGAs, and custom ASICs to large scale cloud-based heterogeneous computing clusters are very good candidates to reach this objective.

This webinar provides the details on the CMC infrastructure specifications for supporting research in:

  • Cloud-based Heterogeneous Computing
  • Implementing Machine Learning algorithms for training and inference


  • A quick recap of artificial intelligence applications and deep learning
  • Heterogeneous computing for deep learning workloads
  • CMC planned heterogeneous computing infrastructure
  • Open Discussion 

By attending this seminar, you will:

  • Learn about lead client project opportunities, and how to enhance your research through early access to advanced technologies
  • Gain early knowledge of upcoming infrastructure in order to plan research activities
  • Influence technology selection (roadmap) and development activities
  • Share insights and experiences with others; explore collaboration opportunities.


Yassine Hariri, PhD, CMC Microsystems

Dr. Yassine Hariri is a senior platform design engineer at CMC Microsystems with over 12 years of experience in implementing embedded as well as cloud based heterogeneous computing platforms, with a focus on hardware architecture, software stack development and validation, design and mapping tools, as well as parallel programming models. He is currently leading projects related to the development, implementation and support of machine learning applications targeting heterogeneous computing systems. Dr. Hariri earned his B.A.Sc. in Computer Engineering from Ecole Marocaine des Sciences de l’ingénieur, Casablanca, Morroco, 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.