Abstract: Presented are embedded control systems with logic for computation and data sharing, methods for making/using such systems, and vehicles with distributed sensors and embedded processing hardware for provisioning automated driving functionality. A method for operating embedded controllers connected with distributed sensors includes receiving a first data stream from a first sensor via a first embedded controller, and storing the first data stream with a first timestamp and data lifespan via a shared data buffer in a memory device. A second data stream is received from a second sensor via a second embedded controller. A timing impact of the second data stream is calculated based on the corresponding timestamp and data lifespan. Upon determining that the timing impact does not violate a timing constraint, the first data stream is purged from memory and the second data stream is stored with a second timestamp and data lifespan in the memory device.

Abstract: Presented are embedded control systems with logic for computation and data sharing, methods for making/using such systems, and vehicles with distributed sensors and embedded processing hardware for provisioning automated driving functionality. A method for operating embedded controllers connected with distributed sensors includes receiving a first data stream from a first sensor via a first embedded controller, and storing the first data stream with a first timestamp and data lifespan via a shared data buffer in a memory device. A second data stream is received from a second sensor via a second embedded controller. A timing impact of the second data stream is calculated based on the corresponding timestamp and data lifespan. Upon determining that the timing impact does not violate a timing constraint, the first data stream is purged from memory and the second data stream is stored with a second timestamp and data lifespan in the memory device.

Abstract: A stream manager for managing the distribution of instructions to a plurality of processing devices includes a dispatcher module configured to: receive multiple instruction streams, wherein each instruction stream includes a plurality of requested computations for processing perception data from a perception data source; partition each instruction stream into a plurality of partitions based on type of device to perform a requested computation from the instruction stream; assign a release time and deadline to each partition, and dispatch partition computations to a plurality of scheduling queues to distribute processing of the partition computations amongst the plurality of processing devices. The plurality of scheduling queues include: a plurality of CPU schedulers, wherein each CPU scheduler is assigned to a specific CPU and a specific scheduling queue; and a plurality of accelerator schedulers, wherein each accelerator scheduler is assigned to a specific scheduling queue and a specific type of accelerator.

Abstract: A stream manager for managing the distribution of instructions to a plurality of processing devices includes a dispatcher module configured to: receive multiple instruction streams, wherein each instruction stream includes a plurality of requested computations for processing perception data from a perception data source; partition each instruction stream into a plurality of partitions based on type of device to perform a requested computation from the instruction stream; assign a release time and deadline to each partition, and dispatch partition computations to a plurality of scheduling queues to distribute processing of the partition computations amongst the plurality of processing devices. The plurality of scheduling queues include: a plurality of CPU schedulers, wherein each CPU scheduler is assigned to a specific CPU and a specific scheduling queue; and a plurality of accelerator schedulers, wherein each accelerator scheduler is assigned to a specific scheduling queue and a specific type of accelerator.