Various examples of a system and method for a storm shutter system is described. In one example, the system includes at least one rail configured to be secured to a building structure and a plurality of panels. Each panel includes a first surface configured to face an exterior environment of a building and a second surface configured to face an interior of the building; at least one perforation extending between the first and second surface; rail connection elements configured to attach the panel to a rail; and interlocking elements configured for panel-to-panel assembly. The panels are configured to be assembled by a single person. The interlocking elements are configured to connect one panel of the plurality of panels to another panel forming a unit of connected panels without using additional hardware.

Various examples of a system and method for a storm shutter system is described. In one example, the system includes at least one rail configured to be secured to a building structure and a plurality of panels. Each panel includes a first surface configured to face an exterior environment of a building and a second surface configured to face an interior of the building; at least one perforation extending between the first and second surface; rail connection elements configured to attach the panel to a rail; and interlocking elements configured for panel-to-panel assembly. The panels are configured to be assembled by a single person. The interlocking elements are configured to connect one panel of the plurality of panels to another panel forming a unit of connected panels without using additional hardware.

Learning-based power modeling of a processor core includes generating, using computer hardware, pipeline snapshot data specifying a plurality of snapshots for a pipeline of a processor core. Each snapshot specifies a state of the pipeline for a clock cycle in executing a computer program over a plurality of clock cycles. A plurality of estimates of power consumption for the processor core in executing the computer program for the plurality of clock cycles are determined, using an instruction-based power model executed by the computer hardware, a based on the pipeline snapshot data. The plurality of estimates of power consumption are calculated using the instruction-based power model based on the plurality of snapshots over the plurality of clock cycles.

A material screening process of generating input features for each material of a subset of materials to be screened, generating target properties for each material of the subset of materials, inputting screening conditions, the input features, and the target properties into a material screening artificial intelligence model and training the material screening artificial intelligence model based on the inputs. Once the model is trained, inputting a dataset of materials to be screened into the trained material screening artificial intelligence model, the dataset of materials includes the subset of materials used to train the model, screening the dataset of materials on the trained material screening artificial intelligence model using the screening conditions and ranking the materials of the dataset based on predicted target properties obtained from the screening.

A material screening process of generating input features for each material of a subset of materials to be screened, generating target properties for each material of the subset of materials, inputting screening conditions, the input features, and the target properties into a material screening artificial intelligence model and training the material screening artificial intelligence model based on the inputs. Once the model is trained, inputting a dataset of materials to be screened into the trained material screening artificial intelligence model, the dataset of materials includes the subset of materials used to train the model, screening the dataset of materials on the trained material screening artificial intelligence model using the screening conditions and ranking the materials of the dataset based on predicted target properties obtained from the screening.

Provided is a simulation method performed by a process simulator, implemented with a recurrent neural network (RNN) including a plurality of process emulation cells, which are arranged in time series and configured to train and predict, based on a final target profile, a profile of each process step included in a semiconductor manufacturing process. The simulation method includes: receiving, at a first process emulation cell, a previous output profile provided at a previous process step, a target profile and process condition information of a current process step; and generating, at the first process emulation cell, a current output profile corresponding to the current process step, based on the target profile, the process condition information, and prior knowledge information, the prior knowledge information defining a time series causal relationship between the previous process step and the current process step.

Provided is a simulation method performed by a process simulator, implemented with a recurrent neural network (RNN) including a plurality of process emulation cells, which are arranged in time series and configured to train and predict, based on a final target profile, a profile of each process step included in a semiconductor manufacturing process. The simulation method includes: receiving, at a first process emulation cell, a previous output profile provided at a previous process step, a target profile and process condition information of a current process step; and generating, at the first process emulation cell, a current output profile corresponding to the current process step, based on the target profile, the process condition information, and prior knowledge information, the prior knowledge information defining a time series causal relationship between the previous process step and the current process step.

Processes for optimizing the geometry of a blade for use in a propeller are disclosed. In one exemplary process, an optimization routine that generates new blade geometries based on structural parameters and calculates performance parameters of each blade geometry, including aerodynamic performance parameters, farfield acoustic parameters, and/or electrical power requirements to operate a propeller having the blade geometry, is performed. The optimization routine receives design parameters and weightings from a user and can use one or more surrogate algorithms to map a design space of the weighted values of the design parameters to find their local minima. The optimization routine then determines an optimized blade geometry using a gradient-based algorithm to generate new blade geometries to explore the minima until the weighted values of the design parameters converge at an optimized blade geometry representing the global minima of the design space.

A compilation system accesses a compilation operations that can be used by a compiler to compile a design under test (DUT). The compilation system can determine a sequence of the compilation operations for the compiler to perform the compilation. The compilation system can detect a failure at a first compilation operation of the sequence of operations during the compilation of the DUT, and the compilation of the DUT can be paused after the failure is detected. The compilation system can determine a second compilation operation of the accessed compilation operations based on one or more netlist parameters of the DUT's netlist. The compilation system then modifies the sequence of compilation operations based on the second compilation operation and resumes the compilation of the DUT at the second compilation operation using the modified sequence of compilation operations.

The present disclosure describes transaction-enabling systems and methods. A system can include a controller and a fleet of machines, each having at least one of a compute task requirement, a networking task requirement, and an energy consumption task requirement. The controller may include a resource requirement circuit to determine an amount of a resource for each of the machines to service the task requirement for each machine, a forward resource market circuit to access a forward resource market, and a resource distribution circuit to execute an aggregated transaction of the resource on the forward resource market.