Abstract:
In embodiments, apparatuses, methods and storage media (transitory and non-transitory) are described that are associated with providing alerts to a caregiver in a vehicle. In various embodiments, an apparatus may include a first sensor coupled with a restraint to provide a restraint indicator, a second sensor coupled with a securing component to provide an attachment indicator, and an alert module operated by one or more processors to cause a wireless transmitter to transmit an alert signal based at least in part on the restraint indicator and the attachment indicator. In various embodiments, a warning apparatus may include an output device and a warning module operated by one or more processors to activate the output device based at least in part on a wireless alert signal from a car seat in a vehicle that indicates the car seat is in use.
Abstract:
Technologies for distributed durable data replication include a computing device having persistent memory that stores a memory state and an update log. The computing device isolates a host partition from a closure partition. The computing device may sequester one or more processor cores for use by the closure partition. The host partition writes transaction records to the update log prior to writing state changes to persistent memory. A replication service asynchronously transmits log records to a remote computing device, which establishes a replica update log in persistent memory. If the host partition fails, the closure partition transmits remaining log records from the update log to the remote computing device. The update log may be quickly replayed when recovering the computing device from failure. The remote computing device may also replay the replica update log to update a remote copy of the state data. Other embodiments are described and claimed.
Abstract:
There is disclosed an example of an artificial intelligence (AI) system, including: a first hardware platform; a fabric interface configured to communicatively couple the first hardware platform to a second hardware platform; a processor hosted on the first hardware platform and programmed to operate on an AI problem; and a first training accelerator, including: an accelerator hardware; a platform inter-chip link (ICL) configured to communicatively couple the first training accelerator to a second training accelerator on the first hardware platform without aid of the processor; a fabric ICL to communicatively couple the first training accelerator to a third training accelerator on a second hardware platform without aid of the processor; and a system decoder configured to operate the fabric ICL and platform ICL to share data of the accelerator hardware between the first training accelerator and second and third training accelerators without aid of the processor.
Abstract:
There is disclosed an example of an artificial intelligence (AI) system, including: a first hardware platform; a fabric interface configured to communicatively couple the first hardware platform to a second hardware platform; a processor hosted on the first hardware platform and programmed to operate on an AI problem; and a first training accelerator, including: an accelerator hardware; a platform inter-chip link (ICL) configured to communicatively couple the first training accelerator to a second training accelerator on the first hardware platform without aid of the processor; a fabric ICL to communicatively couple the first training accelerator to a third training accelerator on a second hardware platform without aid of the processor; and a system decoder configured to operate the fabric ICL and platform ICL to share data of the accelerator hardware between the first training accelerator and second and third training accelerators without aid of the processor.
Abstract:
Detailed are embodiments related to bit matrix multiplication in a processor. For example, in some embodiments a processor comprising: decode circuitry to decode an instruction have fields for an opcode, an identifier of a first source bit matrix, an identifier of a second source bit matrix, an identifier of a destination bit matrix, and an immediate; and execution circuitry to execute the decoded instruction to perform a multiplication of a matrix of S-bit elements of the identified first source bit matrix with S-bit elements of the identified second source bit matrix, wherein the multiplication and accumulation operations are selected by the operation selector and store a result of the matrix multiplication into the identified destination bit matrix, wherein S indicates a plural bit size is described.
Abstract:
A compute device includes one or more processors, one or more resources capable of being utilized by the one or more processors, and a platform interconnect to facilitate communication of messages between the one or more processors and the one or more resources. The compute device is to obtain class of service data for one or more workloads to be executed by the compute device. The class of service data is indicative of a capacity of one or more of the resources to be utilized in the execution of each corresponding workload. The compute device is also to execute the one or more workloads and manage the amount of traffic transmitted through the platform interconnect for each corresponding workload as a function of the class of service data as the one or more workloads are executed.
Abstract:
An apparatus comprising a memory to store an observed trajectory of a pedestrian, the observed trajectory comprising a plurality of observed locations of the pedestrian over a first plurality of timesteps; and a processor to generate a predicted trajectory of the pedestrian, the predicted trajectory comprising a plurality of predicted locations of the pedestrian over the first plurality of timesteps and over a second plurality of timesteps occurring after the first plurality of timesteps; determine a likelihood of the predicted trajectory based on a comparison of the plurality of predicted locations of the pedestrian over the first plurality of timesteps and the plurality of observed locations of the pedestrian over the first plurality of timesteps; and responsive to the determined likelihood of the predicted trajectory, provide information associated with the predicted trajectory to a vehicle to warn the vehicle of a potential collision with the pedestrian.
Abstract:
Examples include techniques to manage training or trained models for deep learning applications. Examples include routing commands to configure a training model to be implemented by a training module or configure a trained model to be implemented by an inference module. The commands routed via out-of-band (OOB) link while training data for the training models or input data for the trained models are routed via inband links.
Abstract:
A computing apparatus, including: a hardware computing platform; and logic to operate on the hardware computing platform, configured to: receive a microservice instance registration for a microservice accelerator, wherein the registration includes a microservice that the microservice accelerator is configured to provide, and a microservice connection capability indicating an ability of the microservice instance to communicate directly with other instances of the same or a different microservice; and log the registration in a microservice registration database.
Abstract:
Technologies for dynamically sharing remote resources include a computing node that sends a resource request for remote resources to a remote computing node in response to a determination that additional resources are required by the computing node. The computing node configures a mapping of a local address space of the computing node to the remote resources of the remote computing node in response to sending the resource request. In response to generating an access to the local address, the computing node identifies the remote computing node based on the local address with the mapping of the local address space to the remote resources of the remote computing node and performs a resource access operation with the remote computing node over a network fabric. The remote computing node may be identified with system address decoders of a caching agent and a host fabric interface. Other embodiments are described and claimed.