The philosophy of ALIGN is to use a mix of algorithmic techniques, template-driven design, and ML. The output of ALIGN is a layout in GDSII format. The ALIGN flow inputs a netlist whose topology and transistor sizes have already been chosen, a set of performance specifications, and a process design kit (PDK) that defines the process technology. Our specific goal is to translate a netlist into a physical layout, with 24-hour turnaround and no human in the loop.
#Analog circuit design software software
Our effort is part of the ALIGN (Analog Layout, Intelligently Generated from Netlists) project, which is developing open-source software for analog/mixed-signal circuit layout. As machine learning (ML) based alternatives have become more viable, alternative forms of solving this problem have begun to be explored. Early approaches to analog design automation attempted to use rule-based methods to capture these variations, but this database of rules required tender care: each new variant might require a new rule. Even so, the number of minor variations within each class is large. A designer manages this complexity by dividing this large set of variants into classes (e.g., OTAs may be telescopic, folded cascode, etc.). For example, the number of topologies of operational transconductance amplifiers (OTAs) easily numbers in the hundreds.
The ability to annotate blocks in a schematic or netlist-level description of a circuit is key to this entire process, but it is a process fraught with complexity due to the large number of variants of each circuit type.
The human designer typically recognizes blocks from a netlist and draws upon her/his experience to translate these blocks into a circuit that is laid out in silicon. At its core, the dificulty of the problem is related to the fact that machine-generated designs have been unable to match the quality of the human designer. The problem of analog design automation has vexed several generations of researchers in electronic design automation.
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