NEW - The presentations of the invited speakers is now available on line (Programme Section)

Machine Learning (ML) has gathered significant visibility recently as an Artificial Intelligence (AI) paradigm, with success in a wide range of applications such as image and speech recognition, autonomous systems, self-driving cars, cyber-physical systems, and many more. The objective therefore of RCML is to promote discussion and stimulate research and ideas towards the potential role of reconfigurable hardware in this important and fast-evolving domain.

The spirit of the workshop is to complement FPL and provide a forum for interesting discussions on a specific topic rather running another specific tailored conference at the same time with FPL. The Organizing Committee, will therefore invite speakers on topic areas such as (but not limited to):
  • Tutorials on emerging issues on machine learning highlighting future challenges and the potential role of programmable hardware in addressing them,
  • Research/design papers detailing FPGA implementations of machine learning training/inference accelerators
  • Unique applications of reconfigurability in machine learning context, domain-specific programmable hardware architectures for machine learning,
  • The potential uses for machine learning techniques within FPGA,
  • Design-flow tools and software.

RCML intends to provide a substantially different event from the well-known conferences and workshops related to reconfigurable computing, by focusing on an informal way to discuss challenges, new fresh ideas, new and future trends, work in progress, etc. and by bringing together leaders in the field to present their views and work from industry and academia, while presenting both an educational and research-stimulating forum.

Along with the main workshop, a poster pitch session will take place for the attendees to present their work and stimulate discussion.(Instructions)

  • Abstract submission deadline (for posters): Friday, July 27, 2018
  • Notification of Acceptance: Friday, August 10, 2018
  • RCML Major Topics of Interest but not limited to:
    • Compilation, Programming Languages, and Domain-Specific Languages supporting machine learning on reconfigurable Systems
    • Tools, Frameworks, Design-flows for Developing ML engines and classification systems
    • Reconfigurable Architectures for ML
    • Communication Infrastructures for ML
    • ML Applications, including Big Data Applications geared for reconfigurable hardware
    • Runtime Adaptability and Potential for On-Line ML
    • Resilience and Reliability Protocols and Architectures
    • Performance Comparisons with other ML Systems (GPUs, CPUs, etc.)
    • Hybrid and Heterogeneous ML Systems
    • ML in education of reconfigurable computing