US 11,106,855 B2 · Pre-characterization mixed-signal design, placement, and routing using machine learning

Abstract

Systems, methods, and devices are disclosed herein for developing a cell design. Operations of a plurality of electrical cells are simulated to collect a plurality of electrical parameters. A machine learning model is trained using the plurality of electrical parameters. The trained machine learning model receives data having cell layout design constraints. The trained machine learning model determines a cell layout for the received data based on the plurality of electrical parameters. The cell layout is provided for further characterization of electrical performance within the cell layout design constraints.

Claims20

Dependent claims

A computer-implemented method comprising:

simulating operations of a plurality of electrical cells to collect a plurality of electrical parameters;
training a machine learning model using the plurality of electrical parameters;
receiving, by the trained machine learning model, data comprising cell layout design constraints;
determining, by the trained machine learning model, a cell layout for the received data based on the plurality of electrical parameters by:
positioning at least two electrical cells of the plurality of electrical cells within the cell layout;
and
generating at least transition cells surrounding the at least two electrical cells, each transition cell surrounding an electrical cell;
and
providing the cell layout for further characterization of electrical performance within the cell layout design constraints.

6 more elements

A computer-implemented method comprising:

receiving, by a trained machine learning model, data comprising cell layout design constraints, wherein the trained machine learning model is trained using a plurality of electrical parameters collected by simulated operations of a plurality of electrical cells;
determining, by the trained machine learning model, a cell layout for the received data based on the plurality of electrical parameters by:
positioning at least two electrical cells of the plurality of electrical cells within the cell layout;
and
generating at least transition cells surrounding the at least two electrical cells, each transition cell surrounding an electrical cell;
and
providing the cell layout for further characterization of electrical performance within the cell layout design constraints.

4 more elements

Dependencies are inferred from the claim text.

Facts

Application

16/572,651Filed 17 Sep 2019

Published

US 2021/0081510 A118 Mar 2021

Granted

31 Aug 2021

Term ends

Not estimatedThe source records don’t support an estimate.

Classification9 codes

G06F 30/392
Circuit design at the physical level: floor-planning or layout, e.g. partitioning or placement
G06F 30/398
Circuit design at the physical level: design verification or optimisation, e.g. using design rule check [DRC], layout versus schematics [LVS] or…
G06F 30/20
Computer-aided design [CAD]: design optimisation, verification or simulation
G06F 30/27
Design optimisation, verification or simulation: using machine learning, e.g. artificial intelligence, neural networks, support vector machines…

Pre-characterization mixed-signal design, placement, and routing using machine learning

Life of this patent

Pre-characterization mixed-signal design, placement, and routing using machine learning

Life of this patent

Abstract

Claims20