AMSNet: Netlist Dataset for AMS Circuits
CoRR(2024)
Abstract
Today's analog/mixed-signal (AMS) integrated circuit (IC) designs demand
substantial manual intervention. The advent of multimodal large language models
(MLLMs) has unveiled significant potential across various fields, suggesting
their applicability in streamlining large-scale AMS IC design as well. A
bottleneck in employing MLLMs for automatic AMS circuit generation is the
absence of a comprehensive dataset delineating the schematic-netlist
relationship. We therefore design an automatic technique for converting
schematics into netlists, and create dataset AMSNet, encompassing
transistor-level schematics and corresponding SPICE format netlists. With a
growing size, AMSNet can significantly facilitate exploration of MLLM
applications in AMS circuit design. We have made an initial set of netlists
public, and will make both our netlist generation tool and the full dataset
available upon publishing of this paper.
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