Abstract: An apparatus to facilitate inferred object shading is disclosed. The apparatus comprises one or more processors to receive rasterized pixel data and hierarchical data associated with one or more objects and perform an inferred shading operation on the rasterized pixel data, including using one or more trained neural networks to perform texture and lighting on the rasterized pixel data to generate a pixel output, wherein the one or more trained neural networks uses the hierarchical data to learn a three-dimensional (3D) geometry, latent space and representation of the one or more objects.

Abstract: Datasets can be synchronized across cloud-based computer environments using computer systems. A data map can be generated for source datasets for a plurality of computing environments, respectively, and an activation function can be determined based on the data map, for simultaneously activating a new dataset of a source system from one of the plurality of computing environments. A generation ID (identification) can be shared from the source system with one or more computing environments of the plurality of the computing environments, in response to receiving the activation function. The new dataset of the source system can be replicated across the one or more computing environments. A data synchronization trigger can be activated, using a synchronization coordinator module of the computer, and the data synchronization can be completed across the plurality of computing environments.

Abstract: Systems, apparatuses and methods may provide for technology that encodes multi-view visual data into latent features via an aggregator encoder, decodes the latent features into one or more novel target views different from views of the multi-view visual data via a rendering decoder, and decodes the latent features into an object label via a label decoder. The operation to decode the latent features via the rendering decoder and to decode the latent features via the label decoder occur at least partially at the same time. The operation to encode, via the aggregator encoder, the multi-view visual data into the latent features further includes operations to: perform, via the aggregator encoder, semantic object recognition operations based on radiance field view synthesis operations, and perform, via the aggregator encoder, radiance field view synthesis operations based on semantic object recognition operations.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to optimize resources in edge networks. An example apparatus includes agent managing circuitry to invoke an exploration agent to identify platform resource devices, select a first one of the identified platform resource devices, and generate first optimization metrics for the workload corresponding to the first one of the identified platform resource devices, the first optimization metrics corresponding to a first path. The example agent is to further select a second one of the identified platform resource devices, generate second optimization metrics for the workload corresponding to the second one of the identified platform resource devices, the second optimization metrics corresponding to a second path.

Abstract: Various embodiments for dynamically generating an advertisement in a video stream are disclosed. In one embodiment, video stream content associated with a video stream for a user device is received. Video analytics data is obtained for the video stream content, which indicates a scene recognized in the video stream content. An advertisement to be generated and inserted into the video stream content is then selected based on the scene recognized in the video stream content, and an advertisement template for generating the selected advertisement is obtained. Video advertisement content corresponding to the advertisement is then generated based on the advertisement template and the video analytics data. The video advertisement content is then inserted into the video stream content, and the modified video stream content is transmitted to the user device.

Abstract: An apparatus and method for scheduling threads on local and remote processing resources.

Abstract: Systems, methods, and apparatuses for resource monitoring identification reuse are described. In an embodiment, a system comprising a hardware processor core to execute instructions storage for a resource monitoring identification (RMID) recycling instructions to be executed by a hardware processor core, a logical processor to execute on the hardware processor core, the logical processor including associated storage for a RMID and state, are described.

Abstract: An apparatus and method for scheduling threads on local and remote processing resources.

Abstract: Embodiments described herein include software, firmware, and hardware that provides techniques to enable deterministic scheduling across multiple general-purpose graphics processing units. One embodiment provides a multi-GPU architecture with uniform latency. One embodiment provides techniques to distribute memory output based on memory chip thermals. One embodiment provides techniques to enable thermally aware workload scheduling. One embodiment provides techniques to enable end to end contracts for workload scheduling on multiple GPUs.

Abstract: Methods, apparatus, systems, and articles of manufacture for dynamic XPU hardware-aware deep learning model management are disclosed. An example method includes extracting a plurality of models from a dataset, respective ones of the plurality of models optimized for a selected quality of service (QoS) objective of a plurality of QoS objectives, identifying a plurality of feature differences between respective ones of the plurality of models, and identifying a plurality of feature similarities between respective ones of the plurality of models.

Abstract: An apparatus to facilitate inferred object shading is disclosed. The apparatus comprises one or more processors to receive rasterized pixel data and hierarchical data associated with one or more objects and perform an inferred shading operation on the rasterized pixel data, including using one or more trained neural networks to perform texture and lighting on the rasterized pixel data to generate a pixel output, wherein the one or more trained neural networks uses the hierarchical data to learn a three-dimensional (3D) geometry, latent space and representation of the one or more objects.

Abstract: Methods, apparatus, systems, and articles of manufacture to perform weight and activation compression and decompression are disclosed. An example apparatus includes memory, instructions in the apparatus, and processor circuitry to execute the instructions to execute a compression operation to obtain compressed data corresponding to weights in a weight matrix, and determine meta-data associated with the weight matrix, a first portion of the meta-data indicative of whether the weight matrix is compressed, a second portion of the meta-data indicative of a cache size of the compressed data, and a third portion of the meta-data indicative of the compression operation executed to obtain the compressed data.

Abstract: An apparatus and method for dynamic resource allocation with mile/performance markers.

Abstract: An apparatus and method for closed loop dynamic resource allocation.

Abstract: Systems, methods, and apparatuses for resource bandwidth monitoring and control are described. For example, in some embodiments, an apparatus comprising a requestor device to send a credit based request, a receiver device to receive and consume the credit based request, and a delay element in a return path between the requestor and receiver devices, the delay element to delay a credit based response from the receiver to the requestor are detailed.

Abstract: Methods, systems, articles of manufacture and apparatus are disclosed to improve autonomous machine capabilities. An example disclosed apparatus includes an agent task manager to retrieve native sensor input data from a sensor of the agent, an agent characteristics engine to identify environmental characteristics based on the retrieved native sensor input data, and a resource allocation modifier to allocate a first quantity of resources of the agent based on a likelihood score associated with the environmental characteristics.

Abstract: An apparatus and method for scheduling threads on local and remote processing resources.

Abstract: An apparatus and method for scheduling threads on local and remote processing resources.

Abstract: Method and apparatus for per-agent control and quality of service of shared resources in a chip multiprocessor platform is described herein. One embodiment of a system includes: a plurality of core and non-core requestors of shared resources, the shared resources to be provided by one or more resource providers, each of the plurality of core and non-core requestors to be associated with a resource-monitoring tag and a resource-control tag; a mapping table to store the resource monitoring and control tags associated with each non-core requestor; and a tagging circuitry to receive a resource request sent from a non-core requestor to a resource provider, the tagging circuitry to responsively modify the resource request to include the resource-monitoring and resource-control tags associated with the non-core requestor in accordance to the mapping table and send the modified resource request to the resource provider.

Abstract: Systems, methods, and apparatuses for resource monitoring identification reuse are described. In an embodiment, a system comprising a hardware processor core to execute instructions storage for a resource monitoring identification (RMID) recycling instructions to be executed by a hardware processor core, a logical processor to execute on the hardware processor core, the logical processor including associated storage for a RMID and state, are described.