Intel Corporation

Siemens Industry Software Gmbh

Nataraj Akkiraju

Ilhami Torunoglu

This application discloses a computing system implementing a mask synthesis system to generate synthetic image clips of design shapes and corresponding mask data for the synthetic image clips. The mask data can describe lithographic masks capable of being used to fabricate the design shapes on an integrated circuit. The mask synthesis system can utilize the synthetic image clips of the design shapes and the corresponding mask data to train a machine-learning system to determine pixelated output masks from portions of the layout design. The mask synthesis system can identify one or more pixelated output masks for portions of a layout design describing an electronic system using the trained machine-learning. The mask synthesis system can synthesize a mask layout design for the electronic system based, at least in part, on the layout design describing the electronic system and the one or more pixelated output masks for the layout design.

Training of machine learning-based inverse lithography technology for mask synthesis with synthetic pattern generation

A method and apparatus for inserting flip-flops in a circuit design between a driver and one or more receiver(s) comprising generating a candidate solution to assign the flip-flop at the node in the circuit, calculating a margin at the driver, calculating the margin at the receiver, and inserting the flip-flop at the node to simultaneously maximize the margin at the driver and the margin at the receiver. Furthermore, the method and apparatus determines whether to insert a second flip-flop at a second node in the circuit, and inserting the second flip-flop at the second node in the circuit such that a delay between the flip-flop and the second flip-flop is substantially equal to a clock period.

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Fremont, CA, United States of America

Nataraj Akkiraju