Automatic compilation method and framework for generating a layout of integrated memory-compute circuit
US-2024403527-A1 · Dec 5, 2024 · US
US2025086368A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2025086368-A1 |
| Application number | US-202218552435-A |
| Country | US |
| Kind code | A1 |
| Filing date | Aug 31, 2022 |
| Priority date | Aug 31, 2022 |
| Publication date | Mar 13, 2025 |
| Grant date | — |
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Provided are a method of verifying process data of a display panel, a device, a storage medium, and a product, which relates to a field of process verification technology. The method of verifying the process data of the display panel includes: generating, based on design data of a process of the display panel, simulation process data for performing the process; performing, by using a process model, a simulation of performing the process based on the simulation process data; and verifying, by using a measurement model, whether the simulation process data is applicable to actual production based on the simulation. The process model is constructed based on actual process data generated in an actual manufacturing process of the display panel, and the measurement model is constructed based on actual process data and actual measurement data which are generated in the actual manufacturing process of the display panel.
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1 . A method of verifying process data of a display panel, comprising: generating, based on design data of a process of the display panel, simulation process data for performing the process; performing, by using a process model, a simulation of performing the process based on the simulation process data; and verifying, by using a measurement model, whether the simulation process data is applicable to actual production based on the simulation, wherein the process model is constructed based on actual process data generated in an actual manufacturing process of the display panel, and the measurement model is constructed based on actual process data and actual measurement data which are generated in the actual manufacturing process of the display panel. 2 . The method of claim 1 , wherein the performing, by using a process model, a simulation of performing the process based on the simulation process data comprises: determining, by using the process model, feature data of the display panel achievable by performing the process based on the simulation process data. 3 . The method of claim 1 , wherein the verifying, by using a measurement model, whether the simulation process data is applicable to actual production based on the simulation, comprises: determining, among the actual process data, actual process data having a similarity higher than a preset similarity threshold with respect to the simulation process data, as similar process data by using the measurement model; determining, among the actual measurement data, feature data of the display panel obtained by actually performing the process based on the similar process data, as actual feature data; and determining that the simulation process data is applicable to actual production, in response to a difference between the actual feature data and the feature data output by the process model being less than a preset difference threshold. 4 . The method of claim 1 , further comprising, before verifying, by using the measurement model, whether the simulation process data is applicable to actual production based on the simulation; calculating a process fluctuation by applying a feedback parameter algorithm to the actual process data by using a control model, and applying the process fluctuation to the feature data output by the process model. 5 . The method of claim 4 , wherein the feedback parameter algorithm comprises one of a moving average algorithm, a weighted moving average algorithm, and or an exponential moving average algorithm. 6 . The method of claim 5 , wherein the moving average algorithm comprises calculating an average value of process parameters of a plurality of consecutive cycles according to an equation: MA = C 1 + C 2 + ⋯ + C n n where each of C 1 , C 2 , . . . C n is a value of the process parameter of a respective cycle, and n is an integer greater than 1. 7 . The method of claim 5 , wherein the weighted moving average algorithm comprises one of a doomsday weighted algorithm, a linear weighted algorithm, a trapezoidal weighted algorithm, and or a square coefficient weighted algorithm. 8 . The method of claim 7 , wherein the doomsday weighted algorithm comprises calculating a weighted average value of process parameters of a plurality of consecutive cycles according to an equation: WMA = C 1 + C 2 + ⋯ + C n × 2 n + 1 where each of C 1 , C 2 , . . . C n is a value of the process parameter of a respective cycle, and n is an integer greater than 1; wherein the linear weighted algorithm comprises calculating a weighted average value of process parameters of a plurality of consecutive cycles according to an equation: WMA = C 1 × 1 + C 2 × 2 + ⋯ + C n × n 1 + 2 + 3 + ⋯ + n where each of C 1 , C 2 , . . . C n is a value of the process parameter of a respective cycle, and n is an integer greater than 1; wherein the trapezoidal weighted algorithm comprises calculating a weighted average value of process parameters of a plurality of consecutive cycles according to an equation: WMA = ( C 1 + C 2 ) × 1 + ( C 2 + C 3 ) × 2 + ⋯ + ( C n - 1
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