Algebraic Machine Learning (AML) offers new opportunities in terms of transparency and control. However, that comes along with many challenges regarding software and hardware implementations. To understand the hardware needs of this new method it is essential to analyze the algorithm and its computational complexity. With this understanding, the final goal of this microproject is to investigate the feasibility of various hardware options particularly in-memory processing hardware acceleration for AML.

Output

Simulation model for a PIM architecture using AML

Report

Project Partners:

  • Algebraic AI S.L., Fernando Martin Maroto
  • Technische Universität Kaiserslautern (TUK), Christian Weis
  • German Research Centre for Artificial Intelligence (DFKI), Matthias Tschöpe

Primary Contact: FERNANDO MARTIN MAROTO, Algebraic AI