Apple Inc.

Meta Platforms, Inc.

Xu Chen

Mohit Narang

Indranil S Sen

Alejandro J Marquez

Shang-Te Yang

Robert William Mayor

Brent Michael Ledvina

Robert W Brumley

William J Bencze

Liangzhen Lai

Harshit Khaitan

Yu Hsin Chen

Miguel Angel Guerrero

Simon James Hollis

Kyong Ho Lee

In one embodiment, a method includes receiving a token indicating a data chunk becomes available in a first circular buffer of a pre-determined size from a direct memory access component, determining that a computation is to be performed with data including the data chunk based on the token, and generating one or more addresses corresponding to one or more data chunks within the first circular buffer that are to be retrieved for the computation, where a generated address is subtracted by the pre-determined size of the first circular buffer when the generated address is greater than a pre-determined maximum associated with the first circular buffer, and where the generated address is added by the pre-determined size of the first circular buffer when the generated address is less than a pre-determined minimum associated with the first circular buffer.

Circular buffer for input and output of tensor computations

Methods and devices are provided for allowing a mobile device (e.g., a key fob or a consumer electronic device, such as a mobile phone, watch, or other wearable device) to interact with a vehicle such that a location of the mobile device can be determined by the vehicle, thereby enabling certain functionality of the vehicle. A device may include both RF antenna(s) and magnetic antenna(s) for determining a location of a mobile device relative to the vehicle. Such a hybrid approach can provide various advantages. Existing magnetic coils on a mobile device (e.g., for charging or communication) may be re-used for distance measurements that are supplemented by the RF measurements. Any device antenna may provide measurements to a machine learning model that determines a region in which the mobile device resides, based on training measurements in the regions.

Enhanced automotive passive entry

Wireless communication between two electronic devices may be used to determine a distance between the two devices, even in the presence of an otherwise-disruptive attacker. A wireless receiver system of one device may receive a true wireless ranging signal from a first transmitting device and a false wireless ranging signal from an attacker. The wireless receiver system may correlate the wireless signals with a known preamble sequence and perform channel estimation using the result, obtaining a channel impulse response for the wireless signals. The wireless receiver system may filter the channel impulse response for the plurality of wireless signals by removing at least part of the channel impulse response due to the false wireless ranging signal while not removing at least part of the channel impulse response due to the true wireless ranging signal. The receiver system may perform a wireless ranging operation using the filtered channel impulse response.

Secure channel estimation architecture

A system including a machine-learning accelerator (MLA) hardware comprising computation-control units that each have a programmable dependency matrix; and a compiler computing module configured to generate, based on a machine-learning model, dependency instructions indicating dependencies between the computation-control units; wherein the computation-control units include at least: a first computation-control unit configured to generate, after completion of a first operation, a synchronization token representing the completion of the first operation, the synchronization token specifying a recipient identifier for an intended recipient computation-control unit of the synchronization token; a second computation-control unit configured to: configure the programmable dependency matrix of the second computation-control unit according to the dependency instructions to include dependency conditions for performing operations; receive the synchronization token based on the recipient identifier; update a dependency state to reflect the received synchronization token; and execute an operation in response to a determination that the dependency state satisfies the dependency condition.

Distributed synchronization scheme

In one embodiment, a method for tensor data distribution using a direct-memory access agent includes generating, by a first controller, source addresses indicating locations in a source memory where portions of a source tensor are stored. A second controller may generate destination addresses indicating locations in a destination memory where portions of a destination tensor are to be stored. The direct-memory access agent receives a source address generated by the first controller and a destination address generated by the second controller and determines a burst size. The direct-memory access agent may issue a read request comprising the source address and the burst size to read tensor data from the source memory and may store the tensor data into an alignment buffer. The direct-memory access agent then issues a write request comprising the destination address and the burst size to write data from the alignment buffer into the destination memory.

Tensor data distribution using grid direct-memory access (DMA) controller

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San Jose, CA, United States of America

Xu Chen