Abstract: An apparatus to facilitate machine learning matrix processing is disclosed. The apparatus comprises a memory to store matrix data one or more processors to execute an instruction to examine a message descriptor included in the instruction to determine a type of matrix layout manipulation operation that is to be executed, examine a message header included in the instruction having a plurality of parameters that define a two-dimensional (2D) memory surface that is to be retrieved, retrieve one or more blocks of the matrix data from the memory based on the plurality of parameters and a register file including a plurality of registers, wherein the one or more blocks of the matrix data is stored within a first set of the plurality of registers.

Abstract: One embodiment provides for a graphics processing unit (GPU) to accelerate machine learning operations, the GPU comprising an instruction cache to store a first instruction and a second instruction, the first instruction to cause the GPU to perform a floating-point operation, including a multi-dimensional floating-point operation, and the second instruction to cause the GPU to perform an integer operation; and a general-purpose graphics compute unit having a single instruction, multiple thread architecture, the general-purpose graphics compute unit to concurrently execute the first instruction and the second instruction.

Abstract: Systems, apparatuses and methods may include a source device that generates a scene change notification in response to a movement of a camera, modifies an encoding scheme associated with the video content captured by the camera in response to the scene change notification, identifies a full-frame difference threshold, wherein scene analysis information includes frame difference data, and compares the frame difference data to an intermediate threshold that is less than the full-frame difference threshold, wherein the scene change notification is generated when the frame difference data exceeds the intermediate threshold. A sink device may obtain transport quality data associated with video content, modify an output parameter of a display based on the transport quality data, determine a view perspective of a still image containing a plurality of image slices, retrieve only a subset of the plurality of image slices based on the view perspective and decode the retrieved subset.

Abstract: Embodiments are generally directed to cache structure and utilization. An embodiment of an apparatus includes one or more processors including a graphics processor; a memory for storage of data for processing by the one or more processors; and a cache to cache data from the memory; wherein the apparatus is to provide for dynamic overfetching of cache lines for the cache, including receiving a read request and accessing the cache for the requested data, and upon a miss in the cache, overfetching data from memory or a higher level cache in addition to fetching the requested data, wherein the overfetching of data is based at least in part on a current overfetch boundary, and provides for data is to be prefetched extending to the current overfetch boundary.

Abstract: An apparatus to facilitate barrier state save and restore for preemption in a graphics environment is disclosed. The apparatus includes processing resources to execute a plurality of execution threads that are comprised in a thread group (TG) and mid-thread preemption barrier save and restore hardware circuitry to: initiate an exception handling routine in response to a mid-thread preemption event, the exception handling routine to cause a barrier signaling event to be issued; receive indication of a valid designated thread status for a thread of a thread group (TG) in response to the barrier signaling event; and in response to receiving the indication of the valid designated thread status for the thread of the TG, cause, by the thread of the TG having the valid designated thread status, a barrier save routine and a barrier restore routine to be initiated for named barriers of the TG.

Abstract: Methods and apparatus relating to techniques for data compression. In an example, an apparatus comprises a processor receive a data compression instruction for a memory segment; and in response to the data compression instruction, compress a sequence of identical memory values in response to a determination that the sequence of identical memory values has a length which exceeds a threshold. Other embodiments are also disclosed and claimed.

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, an object space adjuster communicatively coupled to the graphics subsystem to adjust an object space parameter based on a screen space parameter, and a sample adjuster communicatively coupled to the graphics subsystem to adjust a sample parameter of the graphics subsystem based on a detected condition. Other embodiments are disclosed and claimed.

Abstract: Embodiments are generally directed to cache structure and utilization. An embodiment of an apparatus includes one or more processors including a graphics processor; a memory for storage of data for processing by the one or more processors; and a cache to cache data from the memory; wherein the apparatus is to provide for dynamic overfetching of cache lines for the cache, including receiving a read request and accessing the cache for the requested data, and upon a miss in the cache, overfetching data from memory or a higher level cache in addition to fetching the requested data, wherein the overfetching of data is based at least in part on a current overfetch boundary, and provides for data is to be prefetched extending to the current overfetch boundary.

Abstract: An apparatus to facilitate exception handling for debugging in a graphics environment is disclosed. The apparatus includes load store pipeline hardware circuitry to: in response to a page fault exception being enabled for a memory access request received from a thread of the plurality of threads, allocate a memory dependency token correlated to a scoreboard identifier (SBID) that is included with the memory access request; send, to memory fabric of the graphics processor, the memory access request comprising the memory dependency token; receive, from the memory fabric in response to the memory access request, a memory access response comprising the memory dependency token and indicating occurrence of a page fault error condition and fault details associated with the page fault error condition; and return the SBID associated with the memory access response and fault details of the page fault error condition to a debug register of the thread.

Abstract: An apparatus to facilitate efficient data sharing for graphics data processing operations is disclosed. The apparatus includes a processing resource to generate a stream of instructions, an L1 cache communicably coupled to the processing resource and comprising an on-page detector circuit to determine that a set of memory requests in the stream of instructions access a same memory page; and set a marker in a first request of the set of memory requests; and arbitration circuitry communicably coupled to the L1 cache, the arbitration circuitry to route the set of memory requests to memory comprising the memory page and to, in response to receiving the first request with the marker set, remain with the processing resource to process the set of memory requests.

Abstract: One embodiment provides a multi-chip module accelerator usable to execute tensor data processing operations a multi-chip module. The multi-chip module may include a memory stack including multiple memory dies and parallel processor circuitry communicatively coupled to the memory stack. The parallel processor circuitry may include multiprocessor cores to execute matrix multiplication and accumulate operations. The matrix multiplication and accumulate operations may include floating-point operations that are configurable to include two-dimensional matrix multiply and accumulate operations involving inputs that have differing floating-point precisions. The floating-point operations may include a first operation at a first precision and a second operation at a second precision. The first operation may include a multiply having at least one 16-bit floating-point input and the second operation may include an accumulate having a 32-bit floating-point input.

Abstract: Apparatuses including a graphics processing unit, graphics multiprocessor, or graphics processor having an error detection correction logic for cache memory or shared memory are disclosed. In one embodiment, a graphics multiprocessor includes cache or local memory for storing data and error detection correction circuitry integrated with or coupled to the cache or local memory. The error detection correction circuitry is configured to perform a tag read for data of the cache or local memory to check error detection correction information.

Abstract: Embodiments described herein include software, firmware, and hardware logic that provides techniques to perform arithmetic on sparse data via a systolic processing unit. One embodiment provides techniques to optimize training and inference on a systolic array when using sparse data. One embodiment provides techniques to use decompression information when performing sparse compute operations. One embodiment enables the disaggregation of special function compute arrays via a shared reg file. One embodiment enables packed data compress and expand operations on a GPGPU. One embodiment provides techniques to exploit block sparsity within the cache hierarchy of a GPGPU.

Abstract: One embodiment provides for a graphics processing unit to accelerate machine-learning operations, the graphics processing unit comprising a multiprocessor having a single instruction, multiple thread (SIMT) architecture, the multiprocessor to execute at least one single instruction; and a first compute unit included within the multiprocessor, the at least one single instruction to cause the first compute unit to perform a two-dimensional matrix multiply and accumulate operation, wherein to perform the two-dimensional matrix multiply and accumulate operation includes to compute a 32-bit intermediate product of 16-bit operands and to compute a 32-bit sum based on the 32-bit intermediate product.

Abstract: One embodiment provides for a general-purpose graphics processing unit comprising a processing array including multiple compute blocks, each compute block including multiple processing clusters and a thread dispatch unit to dispatch threads of a workload to the multiple compute blocks based on a parallelism metric, wherein the thread dispatch unit, based on the parallelism metric, is to perform one of a first operation and a second operation, the first operation to distribute threads across the multiple compute blocks and the second operation is to concentrate threads within one of the multiple compute blocks.

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: Described herein are various embodiments of reducing dynamic power consumption within a processor device. One embodiment provides a technique for dynamic link width adjustment based on throughput demand for client of an interconnect fabric. One embodiment provides for a parallel processor comprising an interconnect fabric including a dynamically configurable bus widths and frequencies.

Abstract: An embodiment of an electronic processing system may include an application processor, persistent storage media communicatively coupled to the application processor, and a graphics subsystem communicatively coupled to the application processor. The graphics subsystem may include a first graphics engine to process a graphics workload, and a second graphics engine to offload at least a portion of the graphics workload from the first graphics engine. The second graphics engine may include a low precision compute engine. The system may further include a wearable display housing the second graphics engine. Other embodiments are disclosed and claimed.

Abstract: In accordance with some embodiments, the render rate is varied across and/or up and down the display screen. This may be done based on where the user is looking in order to reduce power consumption and/or increase performance. Specifically the screen display is separated into regions, such as quadrants. Each of these regions is rendered at a rate determined by at least one of what the user is currently looking at, what the user has looked at in the past and/or what it is predicted that the user will look at next. Areas of less focus may be rendered at a lower rate, reducing power consumption in some embodiments.

Abstract: Methods and apparatus relating to techniques for avoiding cache lookup for cold cache. In an example, an apparatus comprises logic, at least partially comprising hardware logic, to collect user information for a user of a data processing device, generate a user profile for the user of the data processing device from the user information, and set a power profile a processor in the data processing device using the user profile. Other embodiments are also disclosed and claimed.