公开(公告)号：US11798198B2

公开(公告)日：2023-10-24

申请号：US18152643

申请日：2023-01-10

Applicant: Intel Corporation

Inventor： Joydeep Ray ,  Ben Ashbaugh ,  Prasoonkumar Surti ,  Pradeep Ramani ,  Rama Harihara ,  Jerin C. Justin ,  Jing Huang ,  Xiaoming Cui ,  Timothy B. Costa ,  Ting Gong ,  Elmoustapha Ould-ahmed-vall ,  Kumar Balasubramanian ,  Anil Thomas ,  Oguz H. Elibol ,  Jayaram Bobba ,  Guozhong Zhuang ,  Bhavani Subramanian ,  Gokce Keskin ,  Chandrasekaran Sakthivel ,  Rajesh Poornachandran

IPC: G06T9/00 ,  G06F12/02 ,  G06T15/00

CPC classification number: G06T9/002 ,  G06F12/023 ,  G06T15/005 ,  G06F2212/302 ,  G06F2212/401

Abstract: Embodiments are generally directed to compression in machine learning and deep learning processing. An embodiment of an apparatus for compression of untyped data includes a graphical processing unit (GPU) including a data compression pipeline, the data compression pipeline including a data port coupled with one or more shader cores, wherein the data port is to allow transfer of untyped data without format conversion, and a 3D compression/decompression unit to provide for compression of untyped data to be stored to a memory subsystem and decompression of untyped data from the memory subsystem.

公开(公告)号：US11762696B2

公开(公告)日：2023-09-19

申请号：US17520583

申请日：2021-11-05

Applicant: Intel Corporation

Inventor： Abhishek R Appu ,  Altug Koker ,  Balaji Vembu ,  Joydeep Ray ,  Kamal Sinha ,  Prasoonkumar Surti ,  Kiran C. Veernapu ,  Subramaniam Maiyuran ,  Sanjeev S. Jahagirdar ,  Eric J. Asperheim ,  Guei-Yuan Lueh ,  David Puffer ,  Wenyin Fu ,  Nikos Kaburlasos ,  Bhushan M. Borole ,  Josh B. Mastronarde ,  Linda L. Hurd ,  Travis T. Schluessler ,  Tomasz Janczak ,  Abhishek Venkatesh ,  Kai Xiao ,  Slawomir Grajewski

IPC: G06F9/50 ,  G06F1/329 ,  G06F9/48 ,  G06T1/20 ,  G06T1/60 ,  G06T15/00

CPC classification number: G06F9/5016 ,  G06F1/329 ,  G06F9/4893 ,  G06F9/5044 ,  G06T1/20 ,  G06T1/60 ,  G06T15/005 ,  G06T2200/28 ,  Y02D10/00

Abstract: In an example, an apparatus comprises a plurality of execution units comprising at least a first type of execution unit and a second type of execution unit and logic, at least partially including hardware logic, to analyze a workload and assign the workload to one of the first type of execution unit or the second type of execution unit. Other embodiments are also disclosed and claimed.

公开(公告)号：US11748302B2

公开(公告)日：2023-09-05

申请号：US17561427

申请日：2021-12-23

Applicant: Intel Corporation

Inventor： Altug Koker ,  Prasoonkumar Surti ,  David Puffer ,  Subramaniam Maiyuran ,  Guei-Yuan Lueh ,  Abhishek R. Appu ,  Joydeep Ray ,  Balaji Vembu ,  Tomer Bar-On ,  Andrew T. Lauritzen ,  Hugues Labbe ,  John G. Gierach ,  Gabor Liktor

IPC: G06F16/13 ,  G06F9/38 ,  G06F9/30 ,  G06F16/11 ,  G06F16/172 ,  G06F9/46 ,  G06F12/1036 ,  G06F12/1045 ,  G06F12/0831

CPC classification number: G06F16/13 ,  G06F9/30 ,  G06F9/38 ,  G06F9/3836 ,  G06F9/461 ,  G06F16/113 ,  G06F16/172 ,  G06F12/0831 ,  G06F12/1036 ,  G06F12/1045 ,  G06F2201/84

Abstract: In an example, an apparatus comprises a plurality of execution units, and a first memory communicatively couple to the plurality of execution units, wherein the first shared memory is shared by the plurality of execution units and a copy engine to copy context state data from at least a first of the plurality of execution units to the first shared memory. Other embodiments are also disclosed and claimed.

公开(公告)号：US20230252010A1

公开(公告)日：2023-08-10

申请号：US18066436

申请日：2022-12-15

Applicant: Intel Corporation

Inventor： Prasoonkumar Surti ,  Abhishek R. Appu ,  Karol Szerszen ,  Eric Liskay ,  Karthik Vaidyanathan

IPC: G06F16/22 ,  G06N20/00 ,  G06T1/20

CPC classification number: G06F16/2237 ,  G06N20/00 ,  G06T1/20

Abstract: Embodiments are generally directed to compression for compression for sparse data structures utilizing mode search approximation. An embodiment of an apparatus includes one or more processors including a graphics processor to process data; and a memory for storage of data, including compressed data. The one or more processors are to provide for compression of a data structure, including identification of a mode in the data structure, the data structure including a plurality of values and the mode being a most repeated value in a data structure, wherein identification of the mode includes application of a mode approximation operation, and encoding of an output vector to include the identified mode, a significance map to indicate locations at which the mode is present in the data structure, and remaining uncompressed data from the data structure.

公开(公告)号：US11710269B2

公开(公告)日：2023-07-25

申请号：US17876358

申请日：2022-07-28

Applicant: Intel Corporation

Inventor： Travis Schluessler ,  Zack Waters ,  Michael Apodaca ,  Daniel Johnston ,  Jason Surprise ,  Prasoonkumar Surti ,  Subramaniam Maiyuran ,  Peter Doyle ,  Saurabh Sharma ,  Ankur Shah ,  Murali Ramadoss

IPC: G06T15/00 ,  G06T15/40 ,  G06T15/80

CPC classification number: G06T15/005 ,  G06T15/40 ,  G06T15/80 ,  G06T2210/52

Abstract: Position-based rendering apparatus and method for multi-die/GPU graphics processing. For example, one embodiment of a method comprises: distributing a plurality of graphics draws to a plurality of graphics processors; performing position-only shading using vertex data associated with tiles of a first draw on a first graphics processor, the first graphics processor responsively generating visibility data for each of the tiles; distributing subsets of the visibility data associated with different subsets of the tiles to different graphics processors; limiting geometry work to be performed on each tile by each graphics processor using the visibility data, each graphics processor to responsively generate rendered tiles; and wherein the rendered tiles are combined to generate a complete image frame.

公开(公告)号：US11676239B2

公开(公告)日：2023-06-13

申请号：US17303654

申请日：2021-06-03

Applicant: Intel Corporation

Inventor： Joydeep Ray ,  Scott Janus ,  Varghese George ,  Subramaniam Maiyuran ,  Altug Koker ,  Abhishek Appu ,  Prasoonkumar Surti ,  Vasanth Ranganathan ,  Andrei Valentin ,  Ashutosh Garg ,  Yoav Harel ,  Arthur Hunter, Jr. ,  SungYe Kim ,  Mike Macpherson ,  Elmoustapha Ould-Ahmed-Vall ,  William Sadler ,  Lakshminarayanan Striramassarma ,  Vikranth Vemulapalli

IPC: G06T1/20 ,  G06F9/50 ,  G06F12/0806 ,  G06F15/80 ,  G06F17/16 ,  G06F7/544 ,  G06N3/04 ,  G06N3/08 ,  G06N3/084 ,  G06N3/048

CPC classification number: G06T1/20 ,  G06F7/5443 ,  G06F9/5027 ,  G06F12/0806 ,  G06F15/8046 ,  G06F17/16 ,  G06N3/048 ,  G06N3/08 ,  G06N3/084

Abstract: Embodiments described herein include, software, firmware, and hardware logic that provides techniques to perform arithmetic on sparse data via a systolic processing unit. Embodiment described herein provided techniques to skip computational operations for zero filled matrices and sub-matrices. Embodiments additionally provide techniques to maintain data compression through to a processing unit. Embodiments additionally provide an architecture for a sparse aware logic unit.

公开(公告)号：US11670044B2

公开(公告)日：2023-06-06

申请号：US17723328

申请日：2022-04-18

Applicant: Intel Corporation

Inventor： Prasoonkumar Surti ,  Abhishek R. Appu ,  Subhajit Dasgupta ,  Srivallaba Mysore ,  Michael J. Norris ,  Vasanth Ranganathan ,  Joydeep Ray

IPC: G06T15/80 ,  G06T1/20 ,  G06T1/60 ,  G06T15/00

CPC classification number: G06T15/80 ,  G06T1/20 ,  G06T1/60 ,  G06T15/005 ,  G06T2210/52

Abstract: One embodiment provides for a graphics processing unit comprising a processing cluster to perform coarse pixel shading and output shaded coarse pixels for processing by a pixel processing pipeline and a render cache to store coarse pixel data for input to or output from a pixel processing pipeline.

公开(公告)号：US11670041B2

公开(公告)日：2023-06-06

申请号：US17466512

申请日：2021-09-03

Applicant: Intel Corporation

Inventor： Prasoonkumar Surti ,  Abhishek R. Appu ,  Joydeep Ray

IPC: G06T15/50 ,  G06T1/60 ,  G06T11/20 ,  G06T15/80 ,  G06T3/40 ,  G06T11/40

CPC classification number: G06T15/503 ,  G06T1/60 ,  G06T11/203 ,  G06T11/40 ,  G06T15/80 ,  G06T2200/12

Abstract: Systems, apparatuses and methods may provide for technology that selects an anti-aliasing mode for a vertex of a primitive based on a parameter associated with the vertex and generates a coverage mask based on the selected anti-aliasing mode. Additionally, one or more pixels corresponding to the vertex may be shaded based at least partly on the coverage mask, wherein the selected anti-aliasing mode varies across a plurality of vertices in the primitive.

公开(公告)号：US11663774B2

公开(公告)日：2023-05-30

申请号：US17684686

申请日：2022-03-02

Applicant: Intel Corporation

Inventor： Prasoonkumar Surti ,  Karthik Vaidyanathan ,  Murali Ramadoss ,  Michael Apodaca ,  Abhishek Venkatesh ,  Joydeep Ray ,  Abhishek R. Appu

IPC: G06T15/50 ,  G06T15/00 ,  G06T15/80 ,  G06T17/20

CPC classification number: G06T15/503 ,  G06T15/005 ,  G06T15/80 ,  G06T17/205 ,  G06T2200/12

Abstract: Systems, apparatuses and methods may provide away to render edges of an object defined by multiple tessellation triangles. More particularly, systems, apparatuses and methods may provide a way to perform anti-aliasing at the edges of the object based on a coarse pixel rate, where the coarse pixels may be based on a coarse Z value indicate a resolution or granularity of detail of the coarse pixel. The systems, apparatuses and methods may use a shader dispatch engine to dispatch raster rules to a pixel shader to direct the pixel shader to include, in a tile and/or tessellation triangle, one more finer coarse pixels based on a percent of coverage provided by a finer coarse pixel of a tessellation triangle at or along the edge of the object.

公开(公告)号：US20230057492A1

公开(公告)日：2023-02-23

申请号：US17854310

申请日：2022-06-30

Applicant: Intel Corporation

Inventor： Sreenivas Kothandaraman ,  Stephen Junkins ,  Srihari Pratapa ,  Prasoonkumar Surti

IPC: G06T9/00 ,  G06T1/20

Abstract: 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.