Abstract: A method includes: identifying a first design rule check (DRC) violation in a cluster box on an integrated circuit layout; locating a first target cell at a first original location in the cluster box, the first target cell being connected to the first DRC violation; detecting a first plurality of candidate locations for the first target cell in the cluster box; calculating resource costs associated with the first plurality of candidate locations; determining a first relocation location, among the first plurality of candidate locations, associated with a minimum resource cost for the first target cell; and relocating the first target cell from the first original location to the first relocation location.

Abstract: A method includes: training a machine learning model with a plurality of electronic circuit placement layouts; predicting, by the machine learning model, fix rates of design rule check (DRC) violations of a new electronic circuit placement layout; identifying hard-to-fix (HTF) DRC violations among the DRC violations based on the fix rates of the DRC violations of the new electronic circuit placement layout; and fixing, by an engineering change order (ECO) tool, the DRC violations.

Abstract: A method includes: identifying a first design rule check (DRC) violation in a cluster box on an integrated circuit layout; locating a first target cell at a first original location in the cluster box, the first target cell being connected to the first DRC violation; detecting a first plurality of candidate locations for the first target cell in the cluster box; calculating resource costs associated with the first plurality of candidate locations; determining a first relocation location, among the first plurality of candidate locations, associated with a minimum resource cost for the first target cell; and relocating the first target cell from the first original location to the first relocation location.

Abstract: A method includes: training a machine learning model with a plurality of electronic circuit placement layouts; predicting, by the machine learning model, fix rates of design rule check (DRC) violations of a new electronic circuit placement layout; identifying hard-to-fix (HTF) DRC violations among the DRC violations based on the fix rates of the DRC violations of the new electronic circuit placement layout; and fixing, by an engineering change order (ECO) tool, the DRC violations.

Abstract: A method includes: training a machine learning model with a plurality of electronic circuit placement layouts; predicting, by the machine learning model, fix rates of design rule check (DRC) violations of a new electronic circuit placement layout; identifying hard-to-fix (HTF) DRC violations among the DRC violations based on the fix rates of the DRC violations of the new electronic circuit placement layout; and fixing, by an engineering change order (ECO) tool, the DRC violations.

Abstract: A method includes: identifying a first design rule check (DRC) violation in a cluster box on an integrated circuit layout; locating a first target cell at a first original location in the cluster box, the first target cell being connected to the first DRC violation; detecting a first plurality of candidate locations for the first target cell in the cluster box; calculating resource costs associated with the first plurality of candidate locations; determining a first relocation location, among the first plurality of candidate locations, associated with a minimum resource cost for the first target cell; and relocating the first target cell from the first original location to the first relocation location.

Abstract: A method includes: training a machine learning model with a plurality of electronic circuit placement layouts; predicting, by the machine learning model, fix rates of design rule check (DRC) violations of a new electronic circuit placement layout; identifying hard-to-fix (HTF) DRC violations among the DRC violations based on the fix rates of the DRC violations of the new electronic circuit placement layout; and fixing, by an engineering change order (ECO) tool, the DRC violations.

Abstract: A method includes: identifying a first design rule check (DRC) violation in a cluster box on an integrated circuit layout; locating a first target cell at a first original location in the cluster box, the first target cell being connected to the first DRC violation; detecting a first plurality of candidate locations for the first target cell in the cluster box; calculating resource costs associated with the first plurality of candidate locations; determining a first relocation location, among the first plurality of candidate locations, associated with a minimum resource cost for the first target cell; and relocating the first target cell from the first original location to the first relocation location.

Abstract: A method includes: training a machine learning model with a plurality of electronic circuit placement layouts; predicting, by the machine learning model, fix rates of design rule check (DRC) violations of a new electronic circuit placement layout; identifying hard-to-fix (HTF) DRC violations among the DRC violations based on the fix rates of the DRC violations of the new electronic circuit placement layout; and fixing, by an engineering change order (ECO) tool, the DRC violations.

Abstract: A method includes: training a machine learning model with a plurality of electronic circuit placement layouts; predicting, by the machine learning model, fix rates of design rule check (DRC) violations of a new electronic circuit placement layout; identifying hard-to-fix (HTF) DRC violations among the DRC violations based on the fix rates of the DRC violations of the new electronic circuit placement layout; and fixing, by an engineering change order (ECO) tool, the DRC violations.

Abstract: A method includes: identifying a first design rule check (DRC) violation in a cluster box on an integrated circuit layout; locating a first target cell at a first original location in the cluster box, the first target cell being connected to the first DRC violation; detecting a first plurality of candidate locations for the first target cell in the cluster box; calculating resource costs associated with the first plurality of candidate locations; determining a first relocation location, among the first plurality of candidate locations, associated with a minimum resource cost for the first target cell; and relocating the first target cell from the first original location to the first relocation location.

Abstract: A method includes: training a machine learning model with a plurality of electronic circuit placement layouts; predicting, by the machine learning model, fix rates of design rule check (DRC) violations of a new electronic circuit placement layout; identifying hard-to-fix (HTF) DRC violations among the DRC violations based on the fix rates of the DRC violations of the new electronic circuit placement layout; and fixing, by an engineering change order (ECO) tool, the DRC violations.

Abstract: A surface structure for sports protector includes a main body for a sports protector, a CPP film connected to an outer surface of the main body, and a pattern layer located between the CPP film and the main body. The CPP film and the pattern layer are connected to the main body by cutting the CPP film to dimensions corresponding to the main body, applying the pattern layer to an inner side of the CPP film, positioning the CPP film having the pattern layer applied thereto in an injection mould, injecting a plastic material into the mould, and allowing the injected plastic material to cool and mold, so as to form the main body of the sports protector with the CPP film bonded to the molded main body and the pattern layer enclosed between the CPP film and the main body without the risk of being rubbed away.

Abstract: A data storage device comprises a flash memory controller having an interface controller, a buffer, a buffer management device, and a microcontroller therein. The interface controller receives several pieces of data and transfers them to the buffer management device, which temporarily stores the data into the buffer and can read/write data temporarily stored in the buffer. The microcontroller is connected between the buffer and the buffer management device for controlling actions between them. There is also a flash memory storage device with a flash array and an error correction code (ECC) controller therein. The flash array is connected to the buffer management device, and is used to receive and store data. The ECC controller is used to check and correct errors in data. The reliability and speed of data access can thus be enhanced, and bidirectional transmission can also be accomplished.