Intel Corporation

Stephen Junkins

William A Hux

Abhishek R Appu

Joydeep Ray

Altug Koker

David M Puffer

James A Valerio

Prasoonkumar Surti

Subramaniam M Maiyuran

Varghese George

Guei-Yuan Lueh

Mike MacPherson

Jorge E Parra

Chandra S Gurram

Fernando C M Martins

Oliver A Heim

Jason Plumb

Sreenivas Kothandaraman

Junjie Gu

Adam T Lake

Mike B Macpherson

Supratim Pal

Ashutosh Garg

Shubra Marwaha

Timothy R Bauer

Shubh Shah

Konrad Trifunovic

Weiyu Chen

Hong Bin Liao

Lance Raymond Alba

Srihari Pratapa

Karthik Vaidyanathan

Milind Baburao Girkar

Bratin Saha

Carsten Benthin

John H Feit

Gabor Liktor

Sven Woop

Wei-Yu Chen

David M Putzolu

Shoumeng Yan

Ying Gao

Robert Geva

Mohan Rajagopalan

Xiaocheng Zhou

Michael Doyle

Sai Luo

Kaiyu Chen

Joshua Barczak

Stephen H Hunt

Holger Gruen

Ravi Narayanaswamy

Clark F Nelson

Rajiv Deodhar

Won-Jong Lee

Chris L Gorman

William Hux

Tiger Chen

Patrick Xi

Bret G Alfieri

Interleaving of variable bitrate streams for GPU implementations is described. An example of an apparatus includes one or more processors including a graphic processor, the graphics processor including a super-compression encoder pipeline to provide variable width interleaved coding; and memory for storage of data, wherein the graphics processor is to perform parallel dictionary encoding on a bitstream of symbols one of multiple workgroups, the workgroup to employ a plurality of encoders to generate a plurality of token-streams of variable lengths; create a histogram including at least tokens from the plurality of token-streams for the workgroup to generate an optimized entropy code; entropy code each of the plurality of token-streams for the workgroup into an encoded bitstream; and variably interleave the encoded bitstreams to generate an interleaved bitstream and bookkeep a size of the interleaved bitstream.

Interleaving of variable bitrate streams for GPU implementations

Variable width interleaved coding for graphics processing is described. An example of an apparatus includes one or more processors including a graphic processor; and memory for storage of data including data for graphics processing, wherein the graphics processor includes an encoder pipeline to provide variable width interleaved coding and a decoder pipeline to decode the variable width interleaved coding, and wherein the encoder pipeline is to receive a plurality of bitstreams from workgroups; perform parallel entropy encoding on the bitstreams to generate a plurality of encoded bitstreams for each of the workgroups; perform variable interleaving of the bitstreams for each workgroup based at least in part on data requirements for decoding received from the decoder pipeline; and compact outputs for each of the workgroups into a contiguous stream of interleaved data.

Variable width interleaved coding for graphics processing

A processing apparatus includes a processing resource including a general-purpose parallel processing engine and a matrix accelerator. The matrix accelerator includes first circuitry to receive a command to perform operations associated with an instruction, second circuitry to configure the matrix accelerator according to a physical depth of a systolic array within the matrix accelerator and a logical depth associated with the instruction, third circuitry to read operands for the instruction from a register file associated with the systolic array, fourth circuitry to perform operations for the instruction via one or more passes through one or more physical pipeline stages of the systolic array based on a configuration performed by the second circuitry, and fifth circuitry to write output of the operations to the register file associated with the systolic array.

Systolic array of arbitrary physical and logical depth

Apparatus and method for efficient graphics processing including ray tracing. For example, one embodiment of a graphics processor comprises: execution hardware logic to execute graphics commands and render images; an interface to couple functional units of the execution hardware logic to a tiled resource; and a tiled resource manager to manage access by the functional units to the tiled resource, a functional unit of the execution hardware logic to generate a request with a hash identifier (ID) to request access to a portion of the tiled resource, wherein the tiled resource manager is to determine whether a portion of the tiled resource identified by the hash ID exists, and if not, to allocate a new portion of the tiled resource and associate the new portion with the hash ID.

Apparatus and method for efficient graphics processing including ray tracing

Embodiments described herein provided for an instruction and associated logic to enable GPGPU program code to access special purpose hardware logic to accelerate dot product operations. One embodiment provides for a graphics processing unit comprising a fetch unit to fetch an instruction for execution and a decode unit to decode the instruction into a decoded instruction. The decoded instruction is a matrix instruction to cause the graphics processing unit to perform a parallel dot product operation. The GPGPU also includes systolic dot product circuitry to execute the decoded instruction across one or more SIMD lanes using multiple systolic layers, wherein to execute the decoded instruction, a dot product computed at a first systolic layer is to be output to a second systolic layer, wherein each systolic layer includes one or more sets of interconnected multipliers and adders, each set of multipliers and adders to generate a dot product.

Instruction and logic for systolic dot product with accumulate

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.

Coarse grain coherency

Embodiments described herein provided for an instruction and associated logic to enable GPGPU program code to access special purpose hardware logic to accelerate dot product operations. One embodiment provides for a graphics processing unit comprising a fetch unit to fetch an instruction for execution and a decode unit to decode the instruction into a decoded instruction. The decoded instruction is a matrix instruction to cause the graphics processing unit to perform a parallel dot product operation. The GPGPU also includes a systolic dot product unit to execute the decoded instruction across one or more SIMD lanes using multiple systolic layers, wherein to execute the decoded instruction, a dot product computed at a first systolic layer is to be output to a second systolic layer, wherein each systolic layer includes one or more sets of interconnected multipliers and adders, each set of multipliers and adders to generate a dot product.

Methods, systems and data structures produce a rasterizer. A graphical state is detected on a machine architecture. The graphical state is used for assembling a shell rasterizer. The machine architecture is used for selecting replacement logic that replaces portions of shell logic in the shell rasterizer. The machine architecture is used for selectively inserting memory management logic into portions of the shell logic to produce.

Methods, systems, and data structures for generating a rasterizer

A computer system may comprise a computer platform and input-output devices. The computer platform may include a plurality of heterogeneous processors comprising a central processing unit (CPU) and a graphics processing unit) GPU, for example. The GPU may be coupled to a GPU compiler and a GPU linker/loader and the CPU may be coupled to a CPU compiler and a CPU linker/loader. The user may create a shared object in an object oriented language and the shared object may include virtual functions. The shared object may be fine grain partitioned between the heterogeneous processors. The GPU compiler may allocate the shared object to the CPU and may create a first and a second enabling path to allow the GPU to invoke virtual functions of the shared object. Thus, the shared object that may include virtual functions may be shared seamlessly between the CPU and the GPU.

Two way communication support for heterogenous processors of a computer platform

Growing community of inventors

Bend, OR, United States of America

Stephen Junkins