Xilinx, Inc.

Zoox, Inc.

Yu Liu

Chuang Wang

Sonal Santan

Joshua Kriser Cohen

Yenpang Lin

Cheng Zhen

Lizhi Hou

Ralph Michael Kling

Andreas Christian Reschka

Soren T Soe

Stephen P Rozum

Robert Edward Somers

Andrew Lewis King

Min Ma

Yidong Zhang

Remote kernel execution in a heterogeneous computing system can include executing, using a device processor of a device communicatively linked to a host processor, a device runtime and receiving from the host processor within a hardware submission queue of the device, a command. The command requests execution of a software kernel and specifies a descriptor stored in a region of a memory of the device shared with the host processor. In response to receiving the command, the device runtime, as executed by the device processor, invokes a runner program associated with the software kernel. The runner program can map a physical address of the descriptor to a virtual memory address corresponding to the descriptor that is usable by the software kernel. The runner program can execute the software kernel. The software kernel can access data specified by the descriptor using the virtual memory address as provided by the runner program.

Transparent and remote kernel execution in a heterogeneous computing system

An integrated circuit can include a communication endpoint configured to maintain a communication link with a host computer, a queue configured to receive a plurality of host commands from the host computer via the communication link, and a processor configured to execute a device runtime. The processor, responsive to executing the device runtime, is configured to perform validation of the host commands read from the queue and selectively execute the host commands based on a result of the validation on a per host command basis. The host commands are executable by the processor to manage functions of the integrated circuit. The queue is implemented in a region of memory that is shared by the integrated circuit and the host computer.

Extensible device hosted root of trust architecture for integrated circuits

Techniques are discussed for generating a spatial grid based on radar sensor data. The spatial grid may include cells, which may be designated as being occupied, occluded, and/or free space. A cell may be designated as being occupied if radar sensor data is associated with a region of an environment associated with the cell. A field may be designated as being occluded if a region of the environment associated with the cell is obstructed, relative to a radar sensor, by a cell that is designated as being occupied. In some instances, objects may be detected and/or tracked in occluded regions. A cell may be designated as being free space if a region associated with the cell is within a field of view of a radar sensor and is unoccupied and un-occluded. In some instances, the spatial grid may be used to control a vehicle, such as an autonomous vehicle, in the environment.

Radar spatial estimation

Examples herein describe techniques for launching and executing a pipeline formed by heterogeneous processing units. A system on a chip (SoC) can include different hardware elements which form a collection of heterogeneous processing units, such as general purpose processor, programmable logic array, and specialized processors. These processing units are heterogeneous meaning their underlying hardware and techniques for processing data are different, in contrast to a system that using homogeneous processing units. In the embodiments herein, the heterogeneous processing units can be arranged into a pipeline where each stage of the pipeline is performed by one of the processing units.

Heterogeneous execution pipeline across different processor architectures and FPGA fabric

A secondary system operates on a vehicle to avoid a collision when a problem occurs with a primary system. For example, the secondary system may operate independently from the primary system to take over control of the vehicle from the primary system when the secondary system detects a potential collision, when an error occurs with the primary system, and so on. In examples, the primary system may implement first techniques, such as Artificial Intelligence (AI) techniques, to understand an environment around the vehicle and/or instruct the vehicle to move within the environment. In examples, the secondary system may implement second techniques that are based on positioning, velocity, acceleration, etc. of the vehicle and/or objects around the vehicle.

Perception collision avoidance

Sensors, including radar sensors, may be used to detect objects in an environment. In an example, a vehicle may include multiple radar sensors that sense objects around the vehicle, e.g., so the vehicle can navigate relative to the objects. Data from a first of the radar sensors can be analyzed to determine a cluster representing an object. Data received from a second sensor (and additional sensors, as included) at substantially the same time can be analyzed to determine additional points to include in the cluster. In additional examples, the radar sensors can have a different interval, e.g., Doppler interval, and information about the points and the intervals can be used to determine a speed of the object relative to the vehicle.

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Newark, CA, United States of America

Yu Liu