Intel Corporation

Deepak Shashidhar Vembar

Atsuo Kuwahara

Abhishek R Appu

Joydeep Ray

Elmoustapha Ould-Ahmed-Vall

Ankur N Shah

Hugues Labbe

Adam T Lake

Radhakrishnan Venkataraman

Prasoonkumar Surti

Chandrasekaran Sakthivel

Glen J Anderson

Vallabhajosyula S Somayazulu

Paul S Diefenbaugh

Kai Xiao

Giuseppe Beppe Raffa

Brent E Insko

Anupreet S Kalra

Kofi C Whitney

James M Holland

Karthik Veeramani

Lenitra M Durham

Altug Koker

Michael Apodaca

Nikos Kaburlasos

Jeffery S Boles

Zhengmin Li

Ryan Scott Brotman

Jill MacDonald Boyce

Travis T Schluessler

Varghese George

Carl S Marshall

Scott R Janus

Selvakumar Panneer

Jacek Kwiatkowski

Cory J Booth

Sayan Lahiri

Jamie Sherman

Balaji Vembu

Murali Ramadoss

Kamal Sinha

John Charles Weast

Richmond Hicks

Wenyin Fu

Pattabhiraman K

Josh B Mastronarde

Bhushan M Borole

Francisco Javier Fernandez

Vasanth Ranganathan

Linda L Hurd

Hassnaa Moustafa

Shao-Wen Yang

Tomer Bar-On

Katalin Klara Bartfai-Walcott

Mike MacPherson

Yen-kuang Chen

Maruti Gupta Hyde

Philip R Laws

Eve M Schooler

David M Cimini

Arun Raghunath

Johannes Guenther

Sherine Abdelhak

Zhijun Lei

Bradley Alan Jackson

Kathy Yuen

Jessica C McCarthy

Christina R Strong

Darrel K Palke

Ignacio Javier Alvarez

John H Feit

Rajneesh Chowdhury

Carson Brownlee

Nilesh K Jain

Jefferson Amstutz

Vivek Tiwari

Soethiha Soe

Joshua Ekandem

Saurabh Tangri

Philip Muse

Sridhar Uyyala

Aleksander Magi

Jonathan J Huang

Ramune Nagisetty

Pete A Denman

Daniel S Lake

Wen-Ling Huang

Ana P Rosario

Rachel Hinman

Hughes Labbe

Brad Jackson

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.

Graphics system with additional context

One embodiment provides a graphics processor comprising a block of execution resources, a cache memory, a cache memory prefetcher, and circuitry including a programmable neural network unit, the programmable neural network unit comprising a network hardware block including circuitry to perform neural network operations and activation operations for a layer of a neural network, the programmable neural network unit addressable by cores within the block of graphics cores and the neural network hardware block configured to perform operations associated with a neural network configured to determine a prefetch pattern for the cache memory prefetcher.

Graphics architecture including a neural network pipeline

In one example, a head mounted display system includes at least one memory; and at least one processor to execute instructions to: detect a first position and a first view direction of a head of a user based on sensor data generated by at least one of an accelerometer, at least one camera, or a gyroscope at a first point in time; determine a latency associated with a time to cause an image to be presented on the display; determine a predicted position and a predicted view direction of the head of the user at a second point in time based on the latency; render, prior to the second point in time, the image for presentation on the display based on the predicted position and the predicted view direction of the head of the user; and cause the display to present the rendered image.

Optimized display image rendering

In one embodiment, an apparatus comprises a memory and a processor. The memory is to store sensor data captured by one or more sensors associated with a first device. Further, the processor comprises circuitry to: access the sensor data captured by the one or more sensors associated with the first device; determine that an incident occurred within a vicinity of the first device; identify a first collection of sensor data associated with the incident, wherein the first collection of sensor data is identified from the sensor data captured by the one or more sensors; preserve, on the memory, the first collection of sensor data associated with the incident; and notify one or more second devices of the incident, wherein the one or more second devices are located within the vicinity of the first device.

Ubiquitous witness for vehicle incidents

Systems, apparatuses and methods may provide away to enhance an augmented reality (AR) and/or virtual reality (VR) user experience with environmental information captured from sensors located in one or more physical environments. More particularly, systems, apparatuses and methods may provide a way to track, by an eye tracker sensor, a gaze of a user, and capture, by the sensors, environmental information. The systems, apparatuses and methods may render feedback, by one or more feedback devices or display device, for a portion of the environment information based on the gaze of the user.

Sensory enhanced augmented reality and virtual reality device

An apparatus and method for efficiently improving virtual/real interactions in augmented reality. For example, one embodiment of a method comprises: capturing a raw image including depth data; identifying one or more regions of interest based on a detected spatial proximity of one or more virtual objects and one or more real objects; generating a super-resolution map of the one or more regions of interest using machine-learning techniques or results thereof; detecting interactions between the virtual objects and the real objects using the super-resolution map; and performing one or more graphics processing or general purpose processing operations based on the detected interactions.

Super-resolution apparatus and method for virtual and mixed reality

An embodiment of a graphics apparatus may include a focus identifier to identify a focus area, and a color compressor to selectively compress color data based on the identified focus area. Another embodiment of a graphics apparatus may include a motion detector to detect motion of a real object, a motion predictor to predict a motion of the real object, and an object placer to place a virtual object relative to the real object based on the predicted motion of the real object. Another embodiment of a graphics apparatus may include a frame divider to divide a frame into viewports, a viewport prioritizer to prioritize the viewports, a renderer to render a viewport of the frame in order in accordance with the viewport priorities, and a viewport transmitter to transmit a completed rendered viewport. Other embodiments are disclosed and claimed.

Predictive viewport renderer and foveated color compressor

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.

Embodiments are directed to neural network processing for multi-object three-dimensional (3D) modeling. An embodiment of a computer-readable storage medium includes executable computer program instructions for obtaining data from multiple cameras, the data including multiple images, and generating a 3D model for 3D imaging based at least in part on the data from the cameras, wherein generating the 3D model includes one or more of performing processing with a first neural network to determine temporal direction based at least in part on motion of one or more objects identified in an image of the multiple images or performing processing with a second neural network to determine semantic content information for an image of the multiple images.

Neural network processing for multi-object 3D modeling

An embodiment of a graphics apparatus may include a processor, memory communicatively coupled to the processor, and a collaboration engine communicatively coupled to the processor to identify a shared graphics component between two or more users in an environment, and share the shared graphics components with the two or more users in the environment. Embodiments of the collaboration engine may include one or more of a centralized sharer, a depth sharer, a shared preprocessor, a multi-port graphics subsystem, and a decode sharer. Other embodiments are disclosed and claimed.

Collaborative multi-user virtual reality

An embodiment of a graphics apparatus may include a context engine to determine contextual information, a recommendation engine communicatively coupled to the context engine to determine a recommendation based on the contextual information, and a configuration engine communicatively coupled to the recommendation engine to adjust a configuration of a graphics operation based on the recommendation. Other embodiments are disclosed and claimed.

Contextual configuration adjuster for graphics

Hybrid rendering is described for a wearable display that is attached to a tethered computer. In one example a process include determining a position and orientation of a wearable computing device, determining a rate of motion of the wearable computing device, comparing the rate of motion to a threshold, if the rate of motion is above the threshold, then rendering a view of a scene at the wearable computing device using the position and orientation information, and displaying the rendered view of the scene.

Hybrid rendering for a wearable display attached to a tethered computer

Growing community of inventors

Portland, OR, United States of America

Deepak Shashidhar Vembar