Built a machine learning framework to upgrade company’s design-similarity-checking tool.
• Feature Extraction from Verilog designs by their number and type of gates using Python.
• Implemented Python and Linux Commands to format .tcl files for standard output from tool.
• Implemented supervised learning by Pytorch and Sklearn for tool’s engine selection.
• Resulted in a way for tool to pick the fastest engine instead of random selection.