Abstract: Example embodiments relate to methods of increasing a temperature of a computer module to start the computer at environmental temperatures below a threshold temperature. An example embodiment includes receiving, at one or more computing components thermally coupled to a main computer via a liquid-cooled plate, a set of program instructions. The method can also include running the set of program instructions on at least one computing component. Running the set of program instructions on the computing component can generate heat that flows to the main computer via the liquid-cooled plate. The method can additionally include detecting, from at least one thermal sensor coupled to the liquid-cooled plate, a temperature reading indicative of a temperature of the main computer. The method can further include determining that the temperature reading has reached a predetermined temperature threshold and based on the temperature reading reaching the predetermined temperature threshold, powering on the main computer.

Abstract: One example method of testing an electrical device comprises transmitting a data pattern to a memory device of the electrical device by a controller of the electrical device to provide a written data pattern to the memory device, wherein the data pattern replicates a resonant frequency of at least a portion of the electrical device, reading the written data pattern from the memory device with the controller, and comparing the written data pattern to the data pattern.

Abstract: One example method of testing an electrical device comprises transmitting a data pattern to a memory device of the electrical device by a controller of the electrical device to provide a written data pattern to the memory device, wherein the data pattern replicates a resonant frequency of at least a portion of the electrical device, reading the written data pattern from the memory device with the controller, and comparing the written data pattern to the data pattern.

Abstract: Example embodiments relate to methods of increasing a temperature of a computer module to start the computer at environmental temperatures below a threshold temperature. An example embodiment includes receiving, at one or more computing components thermally coupled to a main computer via a liquid-cooled plate, a set of program instructions. The method can also include running the set of program instructions on at least one computing component. Running the set of program instructions on the computing component can generate heat that flows to the main computer via the liquid-cooled plate. The method can additionally include detecting, from at least one thermal sensor coupled to the liquid-cooled plate, a temperature reading indicative of a temperature of the main computer. The method can further include determining that the temperature reading has reached a predetermined temperature threshold and based on the temperature reading reaching the predetermined temperature threshold, powering on the main computer.

Abstract: An optical receiver may include a plurality of photodetectors, a common processed data pipeline, and a plurality of processors. Outputs of the plurality of processors are communicatively coupled to the common processed data pipeline. Each processor is configured to accept input signals from a respective photodetector of the plurality of photodetectors. Each processor is also configured to process the input signals to provide processed data and output the processed data into a data stream of the common processed data pipeline according to one or more predetermined data locations. A method for using the optical receiver and a non-transitory computer readable medium are also described.

Abstract: Example embodiments relate to a lower power linearization of lidar signals. An example embodiment includes a method that includes receiving a sample value output by an analog-to-digital converter (ADC) in a processing unit of a lidar system. The ADC may be configured to digitize an optical signal that is compressed by a gain amplifier. The compression may be based on a transfer function comprising one or more linear portions. The method also includes comparing the sample value to one or more threshold values. The one or more threshold values may correspond respectively to the one or more linear portions. The method further includes selecting, for the sample value and based on the comparing, an inverse gain and an associated intercept. The method additionally includes linearizing the sample value based on the selected inverse gain and the associated intercept.

Abstract: One example system for preventing data loss during memory blackout events comprises a memory device, a sensor, and a controller operably coupled to the memory device and the sensor. The controller is configured to perform one or more operations that coordinate at least one memory blackout event of the memory device and at least one data transmission of the sensor.

Abstract: One example method of testing an electrical device comprises transmitting a data pattern to a memory device of the electrical device by a controller of the electrical device to provide a written data pattern to the memory device, wherein the data pattern replicates a resonant frequency of at least a portion of the electrical device, reading the written data pattern from the memory device with the controller, and comparing the written data pattern to the data pattern.

Abstract: A circuit for performing computations for a neural network comprising multiple neural network (NN) layers. The circuit includes a processing device that provides programming data for performing the computations and a core in data communication with the processing device to receive the programming data. The core includes activation memory that stores inputs for a layer and parameter memory that stores parameters for a first NN layer. The core also includes a rotation unit that rotates accessing the inputs from the activation memory based on the programming data and a computation unit that receives a respective input and a parameter for the first NN layer and generates an output of the first NN layer using the input and the parameter. The core also includes a crossbar unit that causes the output to be stored, in the activation memory, in accordance with a bank assignment pattern.