Abstract: Multi-tile Memory Management for Detecting Cross Tile Access, Providing Multi-Tile Inference Scaling with multicasting of data via copy operation, and Providing Page Migration are disclosed herein. In one embodiment, a graphics processor for a multi-tile architecture includes a first graphics processing unit (GPU) having a memory and a memory controller, a second graphics processing unit (GPU) having a memory and a cross-GPU fabric to communicatively couple the first and second GPUs. The memory controller is configured to determine whether frequent cross tile memory accesses occur from the first GPU to the memory of the second GPU in the multi-GPU configuration and to send a message to initiate a data transfer mechanism when frequent cross tile memory accesses occur from the first GPU to the memory of the second GPU.

Abstract: Embodiments are generally directed to a multi-tile architecture for graphics operations. An embodiment of an apparatus includes a multi-tile architecture for graphics operations including a multi-tile graphics processor, the multi-tile processor includes one or more dies; multiple processor tiles installed on the one or more dies; and a structure to interconnect the processor tiles on the one or more dies, wherein the structure to enable communications between processor tiles the processor tiles.

Abstract: An apparatus to facilitate disaggregated computing for a distributed confidential computing environment is disclosed. The apparatus includes a graphics processing unit (GPU) to: provide a virtual GPU monitor (VGM) to interface over a network with a middleware layer of a client platform, the VGM to interface with the middleware layer using a message passing interface; configure and expose, by the VGM, virtual functions (VFs) of the GPU to the middleware layer of the client platform; intercept, by the VGM, request messages directed to the GPU from the middleware layer, the request messages corresponding to VFs of the GPU to be utilized by the client platform; and generate, by the VGM, a response to the request messages for the middleware client.

Abstract: An apparatus to facilitate disaggregated computing for a distributed confidential computing environment is disclosed. The apparatus includes a source remote direct memory access (RDMA) network interface controller (RNIC); a queue to store a data entry corresponding to an RDMA request between the source RNIC and a sink RNIC; a data buffer to store data for an RDMA transfer corresponding to the RDMA request, the RDMA transfer between the source RNIC and the sink RNIC; and a trusted execution environment (TEE) comprising an authentication tag controller to: initialize a first authentication tag calculated using a first key known between a source consumer generating the RDMA request and the source RNIC; associate the first authentication tag with the data entry as integrity verification; initialize a second authentication tag calculated using a second key; and associate the second authentication tag with the data buffer as integrity verification for the data buffer.

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: An apparatus to facilitate disaggregated computing for a distributed confidential computing environment is disclosed. The apparatus includes one or more processors to: provide a remote GPU middleware layer to act as a proxy for an application stack on a client platform separate from the apparatus; communicate, by the remote GPU middleware layer, with a kernel mode driver of the one or more processors to cause the host memory to be allocated for command buffers and data structures received from the client platform for consumption by a command streamer of a remote GPU of the apparatus; and invoke, by the remote GPU middleware layer, the kernel mode driver to submit a workload generated by the application stack, the workload submitted for processing by the remote GPU using the command buffers and the data structures allocated in the host memory as directed by the command streamer.

Abstract: An apparatus to facilitate disaggregated computing for a distributed confidential computing environment is disclosed. The apparatus includes a programmable integrated circuit (IC) comprising system manager hardware circuitry to: interface, over a network, with a remote application of a client platform, the system manager hardware circuitry to interface with the remote application using a message-based interface; perform resource management of resources of the programmable IC; validate incoming messages to the programmable IC; verify whether a requester is allowed to perform requested actions of the incoming messages that are successfully validated; and manage transfer of data between the programmable IC and the remote application based on successfully verifying the requester.

Abstract: An apparatus to facilitate disaggregated computing for a distributed confidential computing environment is disclosed. The apparatus includes a processor executing a trusted execution environment (TEE) comprising a field-programmable gate array (FPGA) driver to interface with an FPGA device that is remote to the apparatus; and a remote memory-mapped input/output (MMIO) driver to expose the FPGA device as a legacy device to the FPGA driver, wherein the processor to utilize the remote MMIO driver to: enumerate the FPGA device using FPGA enumeration data provided by a remote management controller of the FPGA device, the FPGA enumeration data comprising a configuration space and device details; load function drivers for the FPGA device in the TEE; create corresponding device files in the TEE based on the FPGA enumeration data; and handle remote MMIO reads and writes to the FPGA device via a network transport protocol.

Abstract: An apparatus to facilitate disaggregated computing for a distributed confidential computing environment is disclosed. The apparatus includes a programmable integrated circuit (IC) comprising secure device manager (SDM) hardware circuitry to: receive a tenant bitstream of a tenant and a tenant use policy for utilization of the programmable IC via the tenant bitstream, wherein the tenant use policy is cryptographically bound to the tenant bitstream by a cloud service provider (CSP) authorizing entity and signed with a signature of the CSP authorizing entity; in response to successfully verifying the signature, extract the tenant use policy to provide to a policy manager of the programmable IC for verification; in response to the policy manager verifying the tenant bitstream based on the tenant use policy, configure a partial reconfiguration (PR) region of the programable IC using the tenant bitstream; and associate a slot ID of the PR region with the tenant use policy.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed for super-resolution rendering. An example apparatus includes a data handler to generate a multi-sample control surface (MCS) frame based on a color frame, a feature extractor to obtain features from the color frame, a depth frame, and the MCS frame, a network controller to generate spatial data and temporal data based on the features, and a reconstructor to generate a high-resolution image based on the features, the spatial data, and the temporal data.

Abstract: Embodiments described herein are generally directed to conservative rasterization pipeline configurations that allow EarlyZ to be enabled for conservative rasterization. An embodiment of a method includes a conservative rasterizer receiving a primitive to be rasterized. Based on vertices of the primitive, the rasterizer creates a pixel location stream and inner coverage data, indicative of whether the corresponding pixel is fully covered by the primitive or partially covered by the primitive, for each pixel within the pixel location stream. Based on the inner coverage data, pixels of the pixel location stream are grouped into a first group including those of the pixels that are fully covered by the primitive and a second group including those of pixels that are partially covered by the primitive. Separate pixel shader threads are then launched by the rasterizer for blocks of pixels of the first group and blocks of pixels of the second group.

Abstract: One embodiment provides for a graphics processor comprising a block of graphics compute units, a graphics processor pipeline coupled to the block of graphics compute units, and a programmable neural network unit including one or more neural network hardware blocks. The programmable neural network unit is coupled with the block of graphics compute units and the graphics processor pipeline. The one or more neural network hardware blocks include hardware to perform neural network operations and activation operations for a layer of a neural network. The programmable neural network unit can configure settings of one or more hardware blocks within the graphics processor pipeline based on a machine learning model trained to optimize performance of a set of workloads.

Abstract: The disclosed embodiments generally relate to methods, systems and apparatuses to provide ad hoc digital signage for public or private display. In certain embodiments, the disclosure provides dynamically formed digital signage. In one application, one or more drones are used to project the desired signage. In another application one or more drones are used to form a background to receive the projected image. In still another application, sensors are used to detect audience movement, line of sight or engagement level. The sensor information is then used to arrange the projecting drones or the surface-image drones to further signage presentation.

Abstract: Techniques are disclosed to address issues related to the use of personalized training data to supplement machine learning trained models for Driver Monitoring System (DMS), and the accompanying mechanisms to maintain confidentiality of this personalized training data. The techniques disclosed herein also address issues related to maintaining transparency with respect to collected sensor data used in a DMS. Additionally, the techniques disclosed herein facilitate the generation of a digital representation of a driver for use as supplemental training data for the DMS machine learning trained models, which allow for DMS algorithms to be tailored to individual users.

Abstract: An apparatus to facilitate deep learning based selection of samples for adaptive supersampling is disclosed. The apparatus includes one or more processing elements to: receive training data comprising input tiles and corresponding supersampling values for the input tiles, wherein each input tile comprises a plurality of pixels, and train, based on the training data, a machine learning model to identify a level of supersampling for a rendered tile of pixels.

Abstract: Embodiments described herein are generally directed to conservative rasterization pipeline configurations that allow EarlyZ to be enabled for conservative rasterization.

Abstract: One embodiment provides for a graphics processor comprising a block of graphics compute units, a graphics processor pipeline coupled to the block of graphics compute units, and a programmable neural network unit including one or more neural network hardware blocks. The programmable neural network unit is coupled with the block of graphics compute units and the graphics processor pipeline. The one or more neural network hardware blocks include hardware to perform neural network operations and activation operations for a layer of a neural network. The programmable neural network unit can configure settings of one or more hardware blocks within the graphics processor pipeline based on a machine learning model trained to optimize performance of a set of workloads.

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

Abstract: Described herein is a cloud-based gaming system in which graphics processing operations of a cloud-based game can be performed on a client device. Client-based graphics processing can be enabled in response to a determination that the client includes a graphics processor having a performance that exceeds a minimum threshold. When a game is remotely executed and streamed to a client, the client is configurable to provide network feedback that can be used to adjust execution and/or encoding for the game.

Abstract: An apparatus to facilitate disaggregated computing for a distributed confidential computing environment is disclosed. The apparatus includes one or more processors to facilitate receiving a manifest corresponding to graph nodes representing regions of memory of a remote client machine, the graph nodes corresponding to a command buffer and to associated data structures and kernels of the command buffer used to initialize a hardware accelerator and execute the kernels, and the manifest indicating a destination memory location of each of the graph nodes and dependencies of each of the graph nodes; identifying, based on the manifest, the command buffer and the associated data structures to copy to the host memory; identifying, based on the manifest, the kernels to copy to local memory of the hardware accelerator; and patching addresses in the command buffer copied to the host memory with updated addresses of corresponding locations in the host memory.