Abstract: A system and corresponding method for autonomous driving of a vehicle are provided. The system comprises at least one neural network (NN) that generates at least one output for controlling the autonomous driving. The system further comprises a main data path that routes bulk sensor data to the at least one NN and a low-latency data path with reduced latency relative to the main data path. The low-latency data path routes limited sensor data to the at least one NN which, in turn, employs the limited sensor data to improve performance of the at least one NN's processing of the bulk sensor data for generating the at least one output. Improving performance of the at least one NN's processing of the bulk sensor data enables the system to, for example, identify a safety hazard sooner, enabling the autonomous driving to divert the vehicle and avoid contact with the safety hazard.

Abstract: A system and corresponding method for autonomous driving of a vehicle are provided. The system comprises at least one neural network (NN) that generates at least one output for controlling the autonomous driving. The system further comprises a main data path that routes bulk sensor data to the at least one NN and a low-latency data path with reduced latency relative to the main data path. The low-latency data path routes limited sensor data to the at least one NN which, in turn, employs the limited sensor data to improve performance of the at least one NN's processing of the bulk sensor data for generating the at least one output. Improving performance of the at least one NN's processing of the bulk sensor data enables the system to, for example, identify a safety hazard sooner, enabling the autonomous driving to divert the vehicle and avoid contact with the safety hazard.

Abstract: A system and corresponding method for autonomous driving of a vehicle are provided. The system comprises at least one neural network (NN) that generates at least one output for controlling the autonomous driving. The system further comprises a main data path that routes bulk sensor data to the at least one NN and a low-latency data path with reduced latency relative to the main data path. The low-latency data path routes limited sensor data to the at least one NN which, in turn, employs the limited sensor data to improve performance of the at least one NN's processing of the bulk sensor data for generating the at least one output. Improving performance of the at least one NN's processing of the bulk sensor data enables the system to, for example, identify a safety hazard sooner, enabling the autonomous driving to divert the vehicle and avoid contact with the safety hazard.

Abstract: A system and corresponding method alter memory accesses using machine learning. The system comprises a system controller coupled to a processing system that is coupled to a memory system. The system further comprises a learning system coupled to the system controller. The learning system identifies, via a machine learning process, variations on a manner for altering memory access of the memory system to meet at least one goal. The system controller applies the variations identified to the processing system. The machine learning process employs at least one monitored parameter to converge on a given variation of the variations identified and applied. The at least one monitored parameter is affected by the memory access. The given variation enables the at least one goal to be met, improving the processing system, such as by increasing throughput, reducing latency, reducing power consumption, reducing temperature, etc.

Abstract: A system and corresponding method improve a processing system. The system comprises a first learning system coupled to a system controller. The first learning system identifies variations for altering processing of a processing system to meet at least one goal. The system controller applies the variations identified to the processing system. The system further comprises a second learning system coupled to the system controller. The second learning system determines respective effects of the variations identified and applied. The first learning system converges on a given variation of the variations based on the respective effects determined. The given variation enables the at least one goal to be met, improving the processing system, such as by increasing throughput, reducing latency, reducing power consumption, reducing temperature, etc.

Abstract: A system and corresponding method for autonomous driving of a vehicle are provided. The system comprises at least one neural network (NN) that generates at least one output for controlling the autonomous driving. The system further comprises a main data path that routes bulk sensor data to the at least one NN and a low-latency data path with reduced latency relative to the main data path. The low-latency data path routes limited sensor data to the at least one NN which, in turn, employs the limited sensor data to improve performance of the at least one NN's processing of the bulk sensor data for generating the at least one output. Improving performance of the at least one NN's processing of the bulk sensor data enables the system to, for example, identify a safety hazard sooner, enabling the autonomous driving to divert the vehicle and avoid contact with the safety hazard.

Abstract: Aspects disclosed in the detailed description include communicating low-speed and high-speed parallel bit streams over a high-speed serial bus. In one aspect, a data transmitting circuit converts a low-speed parallel bit stream into a high-speed parallel bit stream and then serializes the converted high-speed parallel bit stream based on a high-speed reference frequency. In another aspect, a data receiving circuit recovers the low-speed parallel bit stream from the high-speed parallel bit stream if the low-speed parallel bit stream is determined to exist in the high-speed parallel bit stream.

Abstract: Aspects disclosed in the detailed description include communicating low-speed and high-speed parallel bit streams over a high-speed serial bus. In one aspect, a data transmitting circuit converts a low-speed parallel bit stream into a high-speed parallel bit stream and then serializes the converted high-speed parallel bit stream based on a high-speed reference frequency. In another aspect, a data receiving circuit recovers the low-speed parallel bit stream from the high-speed parallel bit stream if the low-speed parallel bit stream is determined to exist in the high-speed parallel bit stream.

Abstract: Methods and systems according to one or more embodiments are provided for frequency detection. In an embodiment, a frequency detector is provided that includes a capacitor that discharges or charges responsive to binary states of an input signal.