Abstract: Systems and methods for systems and methods for generating the complete set of IC design layout clips, or any part of the complete set, satisfying usefulness criteria and of a prespecified size. A method includes generating an initial set of integrated circuit (IC) design layout clips as a current set of IC design layout clips. The method includes removing any of IC design layout clips from the current set of IC design layout clips that do not meet the one or more usefulness criteria. The method includes, while a size of the IC design layout clips is less than a desired clip size, generating a new set of IC design layout clips from the current set of IC design layout clips according to every combination of pairs of the design layout clips in the current set of IC design layout clips, and repeating the removing process.

Abstract: Systems and methods for systems and methods for generating the complete set of IC design layout clips, or any part of the complete set, satisfying usefulness criteria and of a prespecified size. A method includes generating an initial set of integrated circuit (IC) design layout clips as a current set of IC design layout clips. The method includes removing any of IC design layout clips from the current set of IC design layout clips that do not meet the one or more usefulness criteria. The method includes, while a size of the IC design layout clips is less than a desired clip size, generating a new set of IC design layout clips from the current set of IC design layout clips according to every combination of pairs of the design layout clips in the current set of IC design layout clips, and repeating the removing process.

Abstract: Aspects of the invention relate to hybrid hotspot detection techniques. The hybrid hotspot detection techniques combine machine learning classification, pattern matching and process simulation. A machine learning model, along with false hotspots and false non-hotspots for pattern matching, is determined based on training patterns. The determined machine learning model is then used to classify patterns in a layout design into three categories: preliminary hotspots, preliminary non-hotspots and potential hotspots. Pattern matching is then employed to identify false positives and false negatives in the first two categories. Process simulation is employed to identify boundary hotspots in the last category.

Abstract: Aspects of the invention relate to machine-learning-based hotspot detection techniques. These hotspot detection techniques employ machine learning models constructed using two feature encoding schemes. When two-level machine learning methods are also employed, a total four machine learning models are constructed: scheme-one level-one, scheme-one level-two, scheme-two level-one and scheme-two level-two. The four models are applied to test patterns to derive scheme-one hotspot information and scheme-two hotspot information, which are then used to determine final hotspot information.

Abstract: Aspects of the invention relate to machine-learning-based hotspot detection techniques. These hotspot detection techniques employ machine learning models constructed using two feature encoding schemes. When two-level machine learning methods are also employed, a total four machine learning models are constructed: scheme-one level-one, scheme-one level-two, scheme-two level-one and scheme-two level-two. The four models are applied to test patterns to derive scheme-one hotspot information and scheme-two hotspot information, which are then used to determine final hotspot information.

Abstract: Aspects of the invention relate to hybrid hotspot detection techniques. The hybrid hotspot detection techniques combine machine learning classification, pattern matching and process simulation. A machine learning model, along with false hotspots and false non-hotspots for pattern matching, is determined based on training patterns. The determined machine learning model is then used to classify patterns in a layout design into three categories: preliminary hotspots, preliminary non-hotspots and potential hotspots. Pattern matching is then employed to identify false positives and false negatives in the first two categories. Process simulation is employed to identify boundary hotspots in the last category.

Abstract: Improving circuit design robustness is based on identifying process sensitive and design critical devices. Design critical devices are identified using circuit design information. Various model-based simulations may be performed on the layout areas associated with the identified design critical devices to extract process sensitive and design critical devices. To make the circuit design more robust, various techniques may be employed to treat the extracted process sensitive and design critical devices.

Abstract: An optical switching matrix, including optical input fibers (12) and optical output fibers (14) oriented substantially perpendicular to each other, moveable mirrors (5, 13) placed at the intersections of the directions defined by the various optical fibers, each mirror (13) being capable of moving in order to reflect a beam coming from an optical input fiber, bound for an optical output fiber, and a set of channels defined between the mirrors, inside which the various beams are propagated before and after having encountered the mirrors. The set of mirrors are made on a first substrate wafer (2) that is covered with a second substrate wafer (20), and the various channels (38) are formed between protruding zones (34) present under the second substrate wafers. The protruding zones include housings (33) inside which the moveable mirrors are able to move.

Abstract: An optical switching matrix, made from a semiconductor-D dielectric-based substrate, comprising: