2 research outputs found
A Functional Block Decomposition Method for Automatic Op-Amp Design
This paper presents a method to decompose an op-amp into its functional
blocks. The method is able to recognize functional blocks on a high level of
abstraction as loads or amplification stages which have a large set of possible
structural implementations. The paper presents a hierarchical library of
functional blocks. With every hierarchy level the structural representation of
the functional blocks becomes more variable while its function emerges. We use
the hierarchical order to automatically compute the functional decomposition of
an op-amp given as a flat netlist. Experimental results will illustrate the
method. The functional block decomposition enables a comprehensive
formalization of design knowledge for computer-aided design of op-amps. This is
the first paper of a selection of three paper on automatic op-amp design. In
[1], the design equations that correspond to the functional blocks are
presented. Based on the op-amp decomposition and the design equation, op-amps
are automatically sized. In [2], an automatic op-amp structure synthesis method
will be presented, which is based on the functional block decomposition
presented in the following and the design equations from [1].Comment: This work has been submitted to the IEEE for possible publication.
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Machine Learning for Electronic Design Automation: A Survey
With the down-scaling of CMOS technology, the design complexity of very
large-scale integrated (VLSI) is increasing. Although the application of
machine learning (ML) techniques in electronic design automation (EDA) can
trace its history back to the 90s, the recent breakthrough of ML and the
increasing complexity of EDA tasks have aroused more interests in incorporating
ML to solve EDA tasks. In this paper, we present a comprehensive review of
existing ML for EDA studies, organized following the EDA hierarchy.Comment: Accepted by TODAES. The first 10 authors are ordered alphabeticall