Abstract: Systems, methods, and devices are described herein for integrated circuit (IC) layout validation. A plurality of IC patterns are collected which include a first set of patterns capable of being manufactured and a second set of patterns incapable of being manufactured. A machine learning model is trained using the plurality of IC patterns. The machine learning model generates a prediction model for validating IC layouts. The prediction model receives data including a set of test patterns comprising scanning electron microscope (SEM) images of IC patterns. Design violations associated with an IC layout are determined based on the SEM images and the plurality of IC patterns. A summary of the design violations is provided for further characterization of the IC layout.

Abstract: Systems, methods, and devices are described herein for integrated circuit (IC) layout validation. A plurality of IC patterns are collected which include a first set of patterns capable of being manufactured and a second set of patterns incapable of being manufactured. A machine learning model is trained using the plurality of IC patterns. The machine learning model generates a prediction model for validating IC layouts. The prediction model receives data including a set of test patterns comprising scanning electron microscope (SEM) images of IC patterns. Design violations associated with an IC layout are determined based on the SEM images and the plurality of IC patterns. A summary of the design violations is provided for further characterization of the IC layout.

Abstract: Systems, methods, and devices are described herein for integrated circuit (IC) layout validation. A plurality of IC patterns are collected which include a first set of patterns capable of being manufactured and a second set of patterns incapable of being manufactured. A machine learning model is trained using the plurality of IC patterns. The machine learning model generates a prediction model for validating IC layouts. The prediction model receives data including a set of test patterns comprising scanning electron microscope (SEM) images of IC patterns. Design violations associated with an IC layout are determined based on the SEM images and the plurality of IC patterns. A summary of the design violations is provided for further characterization of the IC layout.

Abstract: Systems, methods, and devices are described herein for integrated circuit (IC) layout validation. A plurality of IC patterns are collected which include a first set of patterns capable of being manufactured and a second set of patterns incapable of being manufactured. A machine learning model is trained using the plurality of IC patterns. The machine learning model generates a prediction model for validating IC layouts. The prediction model receives data including a set of test patterns comprising scanning electron microscope (SEM) images of IC patterns. Design violations associated with an IC layout are determined based on the SEM images and the plurality of IC patterns. A summary of the design violations is provided for further characterization of the IC layout.

Abstract: Systems, methods, and devices are described herein for a deterministic approach that includes receiving an original layout of a semiconductor device that has a number of layers. A violation of a first design rule associated with a first layer of the number of layers is identified. A design rule compilation includes a plurality of design rules associated with each layer of the number of layers. A plurality of derived layers are generated based upon the plurality of design rules. Each derived layer of the plurality of derived layers includes one or more layers of the number of layers of the semiconductor device in which a physical movement to one layer impacts another layer. A forbidden region associated with a second layer of the plurality of layers is designated. A new layout of the number of layers having oriented differently than the original layout is generated such that no layer protrudes within the forbidden region.

Abstract: Systems, methods, and devices are described herein for a deterministic approach that includes receiving an original layout of a semiconductor device that has a number of layers. A violation of a first design rule associated with a first layer of the number of layers is identified. A design rule compilation includes a plurality of design rules associated with each layer of the number of layers. A plurality of derived layers are generated based upon the plurality of design rules. Each derived layer of the plurality of derived layers includes one or more layers of the number of layers of the semiconductor device in which a physical movement to one layer impacts another layer. A forbidden region associated with a second layer of the plurality of layers is designated. A new layout of the number of layers having oriented differently than the original layout is generated such that no layer protrudes within the forbidden region.

Abstract: A method, system, and computer program product are disclosed for performing RC extraction from the perspective of the block level. A translation mechanism is employed to convert from a full-chip design domain to a block-level design domain. This allows model-based prediction results to be used in the early design implementation flow when parasitic RC and timing extractions are performed, where the model-based prediction results relate to predictions of manufacturing variations such as thickness and topography.

Abstract: A method, system, and computer program product are disclosed for performing RC extraction from the perspective of the block level. A translation mechanism is employed to convert from a full-chip design domain to a block-level design domain. This allows model-based prediction results to be used in the early design implementation flow when parasitic RC and timing extractions are performed, where the model-based prediction results relate to predictions of manufacturing variations such as thickness and topography.