Abstract: In an example, an apparatus comprises a plurality of execution units, and logic, at least partially including hardware logic, to assemble a general register file (GRF) message and hold the GRF message in storage in a data port until all data for the GRF message is received. Other embodiments are also disclosed and claimed.

Abstract: Systems and methods for improving cache efficiency and utilization are disclosed. In one embodiment, a graphics processor includes processing resources to perform graphics operations and a cache controller of a cache memory that is coupled to the processing resources. The cache controller is configured to set an initial aging policy using an aging field based on age of cache lines within the cache memory and to determine whether a hint or an instruction to indicate a level of aging has been received. In one embodiment, the cache memory configured to be partitioned into multiple cache regions, wherein the multiple cache regions include a first cache region having a cache eviction policy with a configurable level of data persistence.

Abstract: A mechanism is described for facilitating intelligent thread scheduling at autonomous machines. A method of embodiments, as described herein, includes detecting dependency information relating to a plurality of threads corresponding to a plurality of workloads associated with tasks relating to a processor including a graphics processor. The method may further include generating a tree of thread groups based on the dependency information, where each thread group includes multiple threads, and scheduling one or more of the thread groups associated a similar dependency to avoid dependency conflicts.

Abstract: One embodiment provides a parallel processor comprising a memory interface and a processing array coupled with the memory interface. The processing array is configured to address memory accessed via the memory interface via a virtual address mapping and includes circuitry to resolve a page fault for the virtual address mapping, wherein each of the multiple compute blocks is separately preemptable.

Abstract: A mechanism is described for facilitating recognition, reidentification, and security in machine learning at autonomous machines. A method of embodiments, as described herein, includes facilitating a camera to detect one or more objects within a physical vicinity, the one or more objects including a person, and the physical vicinity including a house, where detecting includes capturing one or more images of one or more portions of a body of the person. The method may further include extracting body features based on the one or more portions of the body, comparing the extracted body features with feature vectors stored at a database, and building a classification model based on the extracted body features over a period of time to facilitate recognition or reidentification of the person independent of facial recognition of the person.

Abstract: Embodiments described herein provide a graphics, media, and compute device having a tiled architecture composed of a number of tiles of smaller graphics devices. The work distribution infrastructure for such device enables the distribution of workloads across multiple tiles of the device. Work items can be submitted to any one or more of the multiple tiles, with workloads able to span multiple tiles. Additionally, upon completion of a work item, graphics, media, and/or compute engines within the device can readily acquire new work items for execution with minimal latency.

Abstract: An apparatus and method are described for implementing memory management in a graphics processing system. For example, one embodiment of an apparatus comprises: a first plurality of graphics processing resources to execute graphics commands and process graphics data; a first memory management unit (MMU) to communicatively couple the first plurality of graphics processing resources to a system-level MMU to access a system memory; a second plurality of graphics processing resources to execute graphics commands and process graphics data; a second MMU to communicatively couple the second plurality of graphics processing resources to the first MMU; wherein the first MMU is configured as a master MMU having a direct connection to the system-level MMU and the second MMU comprises a slave MMU configured to send memory transactions to the first MMU, the first MMU either servicing a memory transaction or sending the memory transaction to the system-level MMU on behalf of the second MMU.

Abstract: Embodiments provide mechanisms to facilitate compute operations for deep neural networks. One embodiment comprises a graphics processing unit comprising one or more multiprocessors, at least one of the one or more multiprocessors including a register file to store a plurality of different types of operands and a plurality of processing cores. The plurality of processing cores includes a first set of processing cores of a first type and a second set of processing cores of a second type. The first set of processing cores are associated with a first memory channel and the second set of processing cores are associated with a second memory channel.

Abstract: A mechanism is described for facilitating optimization of cache associated with graphics processors at computing devices. A method of embodiments, as described herein, includes introducing coloring bits to contents of a cache associated with a processor including a graphics processor, wherein the coloring bits to represent a signal identifying one or more caches available for use, while avoiding explicit invalidations and flushes.

Abstract: An apparatus and method are described for allocating local memories to virtual machines. For example, one embodiment of an apparatus comprises: a command streamer to queue commands from a plurality of virtual machines (VMs) or applications, the commands to be distributed from the command streamer and executed by graphics processing resources of a graphics processing unit (GPU); a tile cache to store graphics data associated with the plurality of VMs or applications as the commands are executed by the graphics processing resources; and tile cache allocation hardware logic to allocate a first portion of the tile cache to a first VM or application and a second portion of the tile cache to a second VM or application; the tile cache allocation hardware logic to further allocate a first region in system memory to store spill-over data when the first portion of the tile cache and/or the second portion of the file cache becomes full.

Abstract: Embodiments described herein provide a graphics processor that can perform a variety of mixed and multiple precision instructions and operations. One embodiment provides a streaming multiprocessor that can concurrently execute multiple thread groups, wherein the streaming multiprocessor includes a single instruction, multiple thread (SIMT) architecture and the streaming multiprocessor is to execute multiple threads for each of multiple instructions. The streaming multiprocessor can perform concurrent integer and floating-point operations and includes a mixed precision core to perform operations at multiple or mixed precisions and dynamic ranges.

Abstract: The systems, apparatuses and methods may provide a way to adaptively process and aggressively cull geometry data. Systems, apparatuses and methods may provide for processing, by a positional only shading pipeline (POSH), geometry data including surface triangles for a digital representation of a scene. More particularly, systems, apparatuses and methods may provide a way to identify surface triangles in one or more exclusion zones and non-exclusion zones, and cull surface triangles in one or more exclusion zones.

Abstract: An apparatus to facilitate a multiplication circuit based on constituent partial product lookup table is disclosed. The apparatus includes a systolic array to receive first source data and second source data; while the first source data is constant and for each of a plurality of subsets of the second source data: determine whether a pre-computed partial product for the first source data and a subset of the plurality of subsets is stored in a lookup table; responsive to the pre-computed partial product being stored in the lookup table, use the pre-computed partial product as a partial product for the first source data and the subset; and responsive to the pre-computed partial product being absent from the lookup table: compute the partial product for the first source data and the subset; and store the partial product as the pre-computed partial product in the lookup table.

Abstract: An apparatus and method are described for allocating local memories to virtual machines. For example, one embodiment of an apparatus comprises: a command streamer to queue commands from a plurality of virtual machines (VMs) or applications, the commands to be distributed from the command streamer and executed by graphics processing resources of a graphics processing unit (GPU); a tile cache to store graphics data associated with the plurality of VMs or applications as the commands are executed by the graphics processing resources; and tile cache allocation hardware logic to allocate a first portion of the tile cache to a first VM or application and a second portion of the tile cache to a second VM or application; the tile cache allocation hardware logic to further allocate a first region in system memory to store spill-over data when the first portion of the tile cache and/or the second portion of the file cache becomes full.

Abstract: One embodiment provides for a general-purpose graphics processing device comprising a general-purpose graphics processing compute block to process a workload including graphics or compute operations, a first cache memory, and a coherency module enable the first cache memory to coherently cache data for the workload, the data stored in memory within a virtual address space, wherein the virtual address space shared with a separate general-purpose processor including a second cache memory that is coherent with the first cache memory.

Abstract: An apparatus and method are described for managing data which is biased towards a processor or a GPU. For example, an apparatus comprises a processor comprising one or more cores, one or more cache levels, and cache coherence controllers to maintain coherent data in the one or more cache levels; a graphics processing unit (GPU) to execute graphics instructions and process graphics data, wherein the GPU and processor cores are to share a virtual address space for accessing a system memory; a GPU memory addressable through the virtual address space shared by the processor cores and GPU; and bias management circuitry to store an indication for whether the data has a processor bias or a GPU bias, wherein if the data has a GPU bias, the data is to be accessed by the GPU without necessarily accessing the processor's cache coherence controllers.

Abstract: One embodiment provides a graphics processor comprising a system interface and circuitry coupled with the system interface. The circuitry includes an execution resource and a preemption status register. The execution resource is configured to execute an instruction. During execution of the instruction, the execution resource is to receive a request to preempt execution of a thread associated with the instruction and, based on a value stored in the preemption status register, execute at least one additional instruction after receipt of the request to preempt execution of the thread.

Abstract: A mechanism is described for facilitating inference coordination and processing utilization for machine learning at autonomous machines. A method of embodiments, as described herein, includes detecting, at training time, information relating to one or more tasks to be performed according to a training dataset relating to a processor including a graphics processor. The method may further include analyzing the information to determine one or more portions of hardware relating to the processor capable of supporting the one or more tasks, and configuring the hardware to pre-select the one or more portions to perform the one or more tasks, while other portions of the hardware remain available for other tasks.

Abstract: An embodiment of an electronic processing system may include an application processor, persistent storage media communicatively coupled to the application processor, a graphics subsystem communicatively coupled to the application processor, a power budget analyzer to identify a power budget for one or more of the application processor, the persistent storage media, and the graphics subsystem, a target analyzer communicatively coupled to the graphics subsystem to identify a target for the graphics subsystem, and a parameter adjuster to adjust one or more parameters of the graphics subsystem based on one or more of the identified power budget and the identified target.

Abstract: An apparatus to facilitate compute optimization is disclosed. The apparatus includes a mixed precision core including mixed-precision execution circuitry to execute one or more of the mixed-precision instructions to perform a mixed-precision dot-product operation comprising to perform a set of multiply and accumulate operations.