Abstract: A system for handling errors in a neural network includes a neural network processor for executing a neural network associated with use of a vehicle. The neural network processor includes an error detector configured to detect a data error associated with execution of the neural network and a neural network controller configured to receive a report of the data error from the error detector. In response to receiving the report, the neural network controller is further configured to signal that a pending result of the neural network is tainted, without terminating execution of the neural network.

Abstract: A system for handling errors in a neural network includes a neural network processor for executing a neural network associated with use of a vehicle. The neural network processor includes an error detector configured to detect a data error associated with execution of the neural network and a neural network controller configured to receive a report of the data error from the error detector. In response to receiving the report, the neural network controller is further configured to signal that a pending result of the neural network is tainted without terminating execution of the neural network.

Abstract: Systems, apparatuses, and methods for implementing a fastpath microcode sequencer are disclosed. A processor includes at least an instruction decode unit and first and second microcode units. For each received instruction, the instruction decode unit forwards the instruction to the first microcode unit if the instruction satisfies at least a first condition. In one implementation, the first condition is the instruction being classified as a frequently executed instruction. If a received instruction satisfies at least a second condition, the instruction decode unit forwards the received instruction to a second microcode unit. In one implementation, the first microcode unit is a smaller, faster structure than the second microcode unit. In one implementation, the second condition is the instruction being classified as an infrequently executed instruction.

Abstract: A system for handling errors in a neural network includes a neural network processor for executing a neural network associated with use of a vehicle. The neural network processor includes an error detector configured to detect a data error associated with execution of the neural network and a neural network controller configured to receive a report of the data error from the error detector. In response to receiving the report, the neural network controller is further configured to signal that a pending result of the neural network is tainted without terminating execution of the neural network.

Abstract: A system for handling errors in a neural network includes a neural network processor for executing a neural network associated with use of a vehicle. The neural network processor includes an error detector configured to detect a data error associated with execution of the neural network and a neural network controller configured to receive a report of the data error from the error detector. In response to receiving the report, the neural network controller is further configured to signal that a pending result of the neural network is tainted without terminating execution of the neural network.

Abstract: A system for handling errors in a neural network includes a neural network processor for executing a neural network associated with use of a vehicle. The neural network processor includes an error detector configured to detect a data error associated with execution of the neural network and a neural network controller configured to receive a report of the data error from the error detector. In response to receiving the report, the neural network controller is further configured to signal that a pending result of the neural network is tainted without terminating execution of the neural network.

Abstract: A system for handling errors in a neural network includes a neural network processor for executing a neural network associated with use of a vehicle. The neural network processor includes an error detector configured to detect a data error associated with execution of the neural network and a neural network controller configured to receive a report of the data error from the error detector. In response to receiving the report, the neural network controller is further configured to signal that a pending result of the neural network is tainted without terminating execution of the neural network.

Abstract: Systems, apparatuses, and methods for implementing a fastpath microcode sequencer are disclosed. A processor includes at least an instruction decode unit and first and second microcode units. For each received instruction, the instruction decode unit forwards the instruction to the first microcode unit if the instruction satisfies at least a first condition. In one implementation, the first condition is the instruction being classified as a frequently executed instruction. If a received instruction satisfies at least a second condition, the instruction decode unit forwards the received instruction to a second microcode unit. In one implementation, the first microcode unit is a smaller, faster structure than the second microcode unit. In one implementation, the second condition is the instruction being classified as an infrequently executed instruction.

Abstract: A system for handling errors in a neural network includes a neural network processor for executing a neural network associated with use of a vehicle. The neural network processor includes an error detector configured to detect a data error associated with execution of the neural network and a neural network controller configured to receive a report of the data error from the error detector. In response to receiving the report, the neural network controller is further configured to signal that a pending result of the neural network is tainted without terminating execution of the neural network.