Final Exam: Pranav S Murali

America/Los_Angeles
ECE-M306 (University of Washington)

ECE-M306

University of Washington

Scott Hauck, Shih-Chieh Hsu (University of Washington Seattle (US))
Pranav S Murali
    • 12:30 PM 1:30 PM
      Accelerating Electron Diffraction Analysis with Machine Learning Inference on FPGAs. 1h

      Abstract:

      This thesis presents a novel approach to enhance the analysis of crystal structures using Reflection High-Energy Electron Diffraction (RHEED) in material science. Addressing the current bottleneck of lengthy analysis times in existing RHEED systems, this study introduces a high-speed camera-based system design capable of real-time crystal analysis.

      The proposed system leverages a LeNet5-based neural network deployed on an FPGA-based framegrabber to accelerate image processing. Through meticulous optimization efforts including neural network quantization and Vivado optimization directives, the system achieves latencies of 450-750 us, facilitating RHEED image analysis at speeds of up to 1000 Hz. This advancement promises researchers real-time insights into crystal growth processes, empowering timely interventions for desired experimental outcomes.

      Speaker: Pranav Srinivas Murali (University of Washington (US))