Abstract: Systems or methods of the present disclosure may provide for implementing design software that is used to design a configuration for a programmable fabric of a programmable logic device. Implementing the design software includes receiving, at a processor, design configuration details for the configuration. Implementing the design software also includes receiving, at the processor, a plurality of constraints including a thermal constraint for the configuration. Moreover, implementing the design software comprises performing thermal aware resource selection based at least in part on the thermal constraint. Furthermore, implementing the design software includes causing the programmable logic device to be operated to stay within the thermal constraint.

Abstract: Techniques are provided for processing video frames in a process flow that includes first and second computation engines. In an example, the first engine is an artificial intelligence based computation engine, and the second engine is a heuristics-based computation engine. A sequence of frames of a video includes a first and second frames that are two consecutive frames in the sequence. An analyzer determines whether the second frame has non-redundant information relative to the first frame. In response to the determination, the analyzer selects one of the first or second engine for processing at least a section of the second frame. For example, if the second frame has non-redundant information relative to the first frame, at least the section of the second frame is processed by the first engine. If the second frame does not include non-redundant information, the second frame is processed by the second engine.

Abstract: An apparatus, including: an interface configured to receive raw images of one or more objects across a timeseries of frames corresponding to a movement event from a perspective of a vehicle of interest (Vol); and processing circuitry that is configured to: track a change in intensity or direction information represented in motion vectors (MVs) generated based on the raw images; generate, based on the change in the intensity or direction information, a weight of an influence vector representing a Vol influence on the movement event; and transmit the weight of the influence vector and an identity of the movement event to an assessment system that is configured to utilize the weight of the influence vector in an assessment of the Vol.

Abstract: Techniques are disclosed to determine driver scoring that consider deviations in map and sensor data in driver score computations. The deviations can be based on deviations from an optimum driving path, and include the determination of vectors between a reference point and one or more landmarks, and one or more reference vectors between the reference point the landmark(s) when traveling on an optimum driving path. A difference between the vectors may then be used determine the deviations from the optimum driving path. In contrast to the conventional approaches, the use of positional deviations (e.g. determined from road markings) in the computation of driver scores allows for improved driver scoring techniques and driver characterizations.

Abstract: Techniques are provided for processing video frames in a process flow that includes first and second computation engines. In an example, the first engine is an artificial intelligence based computation engine, and the second engine is a heuristics-based computation engine. A sequence of frames of a video includes a first and second frames that are two consecutive frames in the sequence. An analyzer determines whether the second frame has non-redundant information relative to the first frame. In response to the determination, the analyzer selects one of the first or second engine for processing at least a section of the second frame. For example, if the second frame has non-redundant information relative to the first frame, at least the section of the second frame is processed by the first engine. If the second frame does not include non-redundant information, the second frame is processed by the second engine.

Abstract: A method for estimating power consumption of a design block of an integrated circuit includes obtaining power consumption data from designs of older-generation microprocessors, selecting a set of power consumption parameters, applying a curve-fitting technique on the obtained power consumption data for the selected set of power consumption parameters, creating a new power consumption model based on the curve-fitting technique and one or more of the power consumption parameters, using the model at a register transfer level of a newer-generation microprocessor to represent estimates of register transfer level power consumption of the newer-generation microprocessor, and outputting the register transfer level power consumption estimates based on the model.

Abstract: A method for estimating power consumption of a design block of an integrated circuit includes obtaining power consumption data from designs of older-generation microprocessors, selecting a set of power consumption parameters, applying a curve-fitting technique on the obtained power consumption data for the selected set of power consumption parameters, creating a new power consumption model based on the curve-fitting technique and one or more of the power consumption parameters, using the model at a register transfer level of a newer-generation microprocessor to represent estimates of register transfer level power consumption of the newer-generation microprocessor, and outputting the register transfer level power consumption estimates based on the model.