Abstract: A system comprises data processing hardware and memory hardware. The memory hardware is in communication with the data processing hardware, and stores instructions that, when executed on the data processing hardware, cause the data processing hardware to perform a plurality of operations. In some examples, one of the operations may include receiving instance management configuration data for a single-tenant software-as-a-service (SaaS) application. Another operation may include further include receiving an image of the single-tenant SaaS application. Yet another operation can include generating, by the control plane manager, a control plane based on the instance management configuration data. The control plane is configured to create multiple instances of the single-tenant SaaS application based on the received image, and to manage the instances of the single-tenant SaaS application based on the received instance management configuration data.

Abstract: An apparatus and method of synthesizing a photolithographic data set includes using a first computational model to calculate a first figure-of-merit for the photolithographic data set; changing a first part of the photolithographic data set to increase the first figure-of-merit; and then using a second computational model to calculate a second figure-of-merit of the photolithographic data set; and changing a second part of the photolithographic data set to increase the second figure-of-merit. The second computational model enables figure-of-merit calculations to be executed at a significantly faster execution rate than the first computational model.

Abstract: A method of modifying polygons in a data set mask-less or mask based optical projection lithography includes: 1) mapping the data set to a figure-of-demerit; 2) moving individual polygon edges to decrease the figure-of-demerit; and 3) disrupting the set of polygons to enable a further decrease in the figure-of-demerit, wherein disrupting polygons includes any of the following polygon disruptions: breaking up, merging, or deleting polygons.

Abstract: A method for generating an OPC model is provided which takes into consideration across-wafer variations which occur during the process of manufacturing semiconductor chips. More particularly, a method for generating an OPC model is provided which takes into consideration across-wafer variations which occur during the process of manufacturing semiconductor chips based on the parameters of test patterns measured at the “wafer sweet spots” so as to arrive at an accurate model.

Abstract: A method for generating an OPC model is provided which takes into consideration across-wafer variations which occur during the process of manufacturing semiconductor chips. More particularly, a method for generating an OPC model is provided which takes into consideration across-wafer variations which occur during the process of manufacturing semiconductor chips based on the parameters of test patterns measured at the “wafer sweet spots” so as to arrive at an accurate model.

Abstract: A method of modifying polygons in a data set mask-less or mask based optical projection lithography includes: 1) mapping the data set to a figure-of-demerit; 2) moving individual polygon edges to decrease the figure-of-demerit; and 3) disrupting the set of polygons to enable a further decrease in the figure-of-demerit, wherein disrupting polygons includes any of the following polygon disruptions: breaking up, merging, or deleting polygons.

Abstract: An apparatus and method of synthesizing a photolithographic data set includes using a first computational model to calculate a first figure-of-merit for the photolithographic data set; changing a first part of the photolithographic data set to increase the first figure-of-merit; and then using a second computational model to calculate a second figure-of-merit of the photolithographic data set; and changing a second part of the photolithographic data set to increase the second figure-of-merit. The second computational model enables figure-of-merit calculations to be executed at a significantly faster execution rate that the first computational model.