mflowgen

Alex Carsello, James Thomas, Ankita Nayak, Po-Han Chen, Mark Horowitz, Priyanka Raina, Christopher Torng
2022 Proceedings of the 59th ACM/IEEE Design Automation Conference  
Achieving high code reuse in physical design flows is challenging but increasingly necessary to build complex systems. Unfortunately, existing approaches based on parameterized Tcl generators support very limited reuse as designers customize flows for specific designs and technologies, preventing their reuse in future flows. We present a vision and framework based on modular flow generators that encapsulates coarse-grained and fine-grained reusable code in modular nodes and assembles them into
more » ... omplete flows. The key feature is a flow consistency and instrumentation layer embedded in Python, which supports mechanisms for rapid and early feedback on inconsistent composition. We evaluate the design flows of successive generations of silicon prototypes built in TSMC16, TSMC28, TSMC40, SKY130, and IBM180 technologies, showing how our approach can enable significant code reuse in future flows.
doi:10.1145/3489517.3530633 fatcat:eyfteogjgrcezdencwsnxjgb44