Abstract: Methods, systems, and apparatuses related to reducing network congestion by analyzing data using a lightweight artificial intelligence (AI) layer prior to transmission are described. An AI model may predictively select data that need not be transmitted and, in some embodiments, further process data to be transmitted. As a result, the total size and amount of data transmitted over the network can be reduced, while the data needs of the receiving device can still be met. For example, data generated by a source application may be received and input into a predictive model, which may generate a prediction output for the data. The data may be pre-processed using a strategy selected based on the prediction output, and the pre-processed data may be transmitted over a network to a server.

Abstract: A computing system has a processing device (e.g., CPU, FPGA, or GPU) and memory regions (e.g., in a DRAM device) used by the processing device during normal operation. The computing system is configured to: monitor use of the memory regions in volatile memory; based on monitoring the use of the memory regions, identify at least one of the memory regions of the volatile memory; initiate a hibernation process; and during the hibernation process, copy data stored in the identified memory regions to non-volatile memory.

Abstract: A method includes performing a copyback operation comprising transferring, using an internal processing device, user data and header data corresponding to the user data from a first block of memory in a memory device to a register in the memory device, decoupling the user data from the header data, performing an error correction code (ECC) operation on updated header data using an external processing device, transferring, via the external processing device, the updated header data to the register, and transferring the user data and the updated header data from the register to a second block of memory in the memory device.

Abstract: Systems, methods, and apparatus related to protecting data stored in volatile memory of a computing system during a standby mode. In one approach, a first signature is generated for data stored in volatile memory. In some cases, the stored data may include sensor data obtained from one or more sensors of a vehicle, mobile device or other electronic device. The first signature is stored in a non-volatile memory device, and then the computing system enters the standby mode. Subsequently, after exiting the standby mode, a second signature is generated for the data stored in the volatile memory. The first signature is read from the non-volatile memory device and compared to the second signature. A signature mismatch indicates that an unintended change has occurred in the stored data during the standby mode. One or more remedial actions are performed by the computing system in response to this signature mismatch.

Abstract: The disclosed embodiments are directed to improving the lifespan of a memory device. In one embodiment, a system is disclosed comprising: a host processor and a memory device, wherein the host processor is configured to receive a write command from a virtual machine, identify a region identifier associated with the virtual machine, augment the write command with the region identifier, and issue the write command to the memory device, and the memory device is configured to receive the write command, identify a region comprising a subset of addresses writable by the memory device using a region configuration table, and write the data to an address in the subset of addresses.

Abstract: Disclosed are devices and methods for improving the initialization of devices housing memories. In one embodiment, a method is disclosed comprising writing a test program to a first region of a memory device during production of the memory device; executing a self-test program in response to detecting a first power up of the memory device, the self-test program stored within the test program; and retrieving and installing an image from a remote data source in response to detecting a subsequent power up of the memory device, the retrieving performed by the test program.

Abstract: The disclosed embodiments are directed to adjusting the operational characteristics of a black box installed in a vehicle. In one embodiment a method is disclosed comprising classifying a mental state of a driver of an automobile, loading at least one setting based on the mental state, the setting defining an operational characteristic of a black box installed in the automobile, configuring the black box using the at least one setting, and recording one or more events by the black box.

Abstract: A computing system has a first processing device (e.g., CPU, FPGA, or GPU) and memory regions (e.g., in a DRAM device) used by the processing device during normal operation. In one approach, the computing system is configured to: collect data associated with operation of an autonomous vehicle; monitor, by a first processing device, the collected data; and based on the monitoring, determine that an event on the autonomous vehicle has occurred. The computing system is further configured to, in response to determining that the event has occurred, initiate a transfer of data controlled by a second processing device, the transfer including copying data stored in volatile memory of the autonomous vehicle to non-volatile memory of the autonomous vehicle, wherein the second processing device controls copying of the data independently of the first processing device.

Abstract: The disclosed embodiments relate to logging activities of memory devices and adjusting the operation of a controller based on the activities. In one embodiment, a method comprises collecting, by a memory device, profile data, the profile data associated with read and write commands and corresponding address information issued to the memory device from a host device; storing, by the memory device, the profile data in a portion of a storage array managed by the memory device; receiving, by the memory device, an update generated based on the profile data, the update adjusting a configuration setting of the memory device; and processing, by the memory device, a received command based on the configuration setting.

Abstract: The disclosed embodiments relate to logging activities of memory devices and adjusting the operation of a controller based on the activities. In one embodiment, a method comprises monitoring, by a memory device, die temperatures and data sizes of commands issued to the memory device; determining, by the memory device, a target size for a buffer based on the die temperatures and data sizes; and adjusting, by the memory device, a current size of the buffer to meet the target size.

Abstract: Systems, methods, and apparatus related to determining ice hazards on roads based on crowdsourced data from vehicles. In one approach, a server receives weather data and location data from each of several vehicles. The weather data is timestamped when received. The server determines, using the location data, a geographic region in which each vehicle is located. The weather data is stored in a database associated with the respective geographic region for the vehicle that transmitted the weather data. The server periodically scans the database to select weather data received over a selected time period. The selected data is analyzed to determine whether an ice hazard exists for one or more regions. A communication is sent to vehicles in those regions having the determined ice hazard.

Abstract: A system includes a processing device and trigger circuitry to signal the processing device responsive, at least in part, based on a determination that a trigger event has occurred. The system can further include a memory device communicatively coupled to the processing device. The memory device can include a cyclic buffer partition portion having a first endurance characteristic and a first reliability characteristic associated therewith. The memory device can further include a snapshot partition portion coupled to the cyclic buffer partition portion via hold-up capacitors. The snapshot partition portion can have a second endurance characteristic and a second reliability characteristic associated therewith. The processing device can perform operations including writing received data sequentially to the cyclic buffer partition portion and writing, based at least in part on the determination that the trigger event has occurred, data from the cyclic buffer partition portion to the snapshot partition portion.

Abstract: Instructions can be executed to determine a quantity of logical units that are part of a memory device. The instructions can be executed to operate the logical units with a programming time sufficient to provide a required throughput for storage of time based telemetric sensor data received from a host. The instructions can be executed to operate the logical units with a trim that correspond to the programming time.

Abstract: A system includes a memory device and a processing device coupled to the memory device. The processing device can determine a data rate from a first sensor and a data rate from a second sensor. The processing device can write a first set of data received from the first sensor at a first logical block address (LBA) in the memory device. The processing device can write a second set of data received from the second sensor and subsequent to the first set of data at a second LBA in the memory device. The processing device can remap the first LBA and the second LBA to be logically sequential LBAs. The second LBA can be associated with an offset from the first LBA and the offset can correspond to a data rate of the first sensor.

Abstract: A memory component comprises a cyclic buffer partition portion and a snapshot partition portion. In response to receiving a signal that a trigger event has occurred, a processing device included in the memory component performs an error correction operation on a portion of data stored in the cyclic buffer partition portion, copies the data stored in the cyclic buffer partition portion to the snapshot partition portion in response to the error correction operation being successful, and sends the data stored in the cyclic buffer partition portion to a processing device operatively coupled to the memory component in response to the error correction operation not being successful.

Abstract: A system including sensors of an advanced driver assistance system and a data recorder. The data recorder has: a volatile memory; a non-volatile memory configured with a file system region and a buffer region; and a processor configured to implement a file system mounted in the file system region. The data recorder records outputs from the sensors via the volatile memory into the buffer region in a cyclic way and, in response to an event, retrieve sensor data from the buffer region and store the sensor data into files organized under the file system mounted in the file system region.

Abstract: Systems, methods and apparatus to collect sensor data generated in an autonomous vehicle. Sensors in the vehicle generate a sensor data stream during operations of the vehicle on a road. An advanced driver assistance system (ADAS) of the vehicle uses the sensor data stream to operate the vehicle and generate a trigger signal in response to a fault in object detection, recognition, identification or classification and/or in response to the detection/prediction of an accident. A cyclic buffer buffers at least a portion of the sensor data stream. In response to the trigger signal, a selected segment of the sensor data stream is stored into a non-volatile memory. The selected segment can be partially before the trigger signal and partially after the trigger signal; and selected segment can be longer than what can be fully buffered in the cyclic buffer at the time of the trigger signal.

Abstract: Methods, systems, and apparatuses related to reducing network congestion by analyzing data using a lightweight artificial intelligence (AI) layer prior to transmission are described. An AI model may predictively select data that need not be transmitted and, in some embodiments, further process data to be transmitted. As a result, the total size and amount of data transmitted over the network can be reduced, while the data needs of the receiving device can still be met. For example, data generated by a source application may be received and input into a predictive model, which may generate a prediction output for the data. The data may be pre-processed using a strategy selected based on the prediction output, and the pre-processed data may be transmitted over a network to a server.

Abstract: A system includes a processing device and a memory device communicatively coupled to the processing device. The memory device can include a cyclic buffer partition portion and a snapshot partition portion coupled to the cyclic buffer partition portion via hold-up capacitors. The snapshot partition portion can further include a first sub-partition portion having a first programming characteristic and a second sub-partition portion having a second programming characteristic. The processing device can write received data sequentially to the cycle buffer partition portion and write, based at least in part on a determination that a trigger event has occurred, data from the cyclic buffer partition portion to the first sub-partition portion or the second sub-partition portion, or both.

Abstract: Instructions can be executed to adjust a trim at first intervals until a quantity of program/erase cycles (PEC) have occurred. The trim defines a valley width between data states. Instructions can be executed to adjust the trim at second intervals, greater than the first intervals, after the quantity of PEC have occurred.