Machine Learning in the Analog Circuit Simulation Loop

Konferenz: SMACD / PRIME 2021 - International Conference on SMACD and 16th Conference on PRIME
19.07.2021 - 22.07.2021 in online

Tagungsband: SMACD / PRIME 2021

Seiten: 4Sprache: EnglischTyp: PDF

Tzenov, Petar; Sokar, Ahmed (Infineon Technologies AG, Neubiberg, Germany)

This paper presents the software coupling of an analog circuit simulator (ACS) to a machine learning (ML) execution engine, in order to enable usage of ML models in circuit simulation context. This is achieved by interfacing Infineon’s in-house simulator, TITAN, with the widely accepted machine learning framework TensorFlow (TF), via an easy to use Verilog-A API. Here we introduce the basic characteristics of this interface and present an application example for its usage in analog circuit behavioral modeling.