Patents by Inventor Linda L. Hurd

Linda L. Hurd has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20190146800
    Abstract: One embodiment provides for a general-purpose graphics processing unit comprising a streaming multiprocessor having a single instruction, multiple thread (SIMT) architecture including hardware multithreading. The streaming multiprocessor comprises multiple processing blocks including multiple processing cores. The processing cores include independent integer and floating-point data paths that are configurable to concurrently execute multiple independent instructions. A memory is coupled with the multiple processing blocks.
    Type: Application
    Filed: December 20, 2018
    Publication date: May 16, 2019
    Applicant: Intel Corporation
    Inventors: ELMOUSTAPHA OULD-AHMED-VALL, BARATH LAKSHMANAN, TATIANA SHPEISMAN, Joydeep Ray, Ping T. Tang, Michael Strickland, Xiaoming Chen, Anbang Yao, Ben J. Ashbaugh, Linda L. Hurd, Liwei Ma
  • Patent number: 10262388
    Abstract: A control surface tracks an individual cacheline in the original surface for frequent data values. If so, control surface bits are set. When reading a cacheline from memory, first the control surface bits are read. If they happen to be set, then the original memory read is skipped altogether and instead the bits from the control surface provide the value for the entire cacheline.
    Type: Grant
    Filed: April 10, 2017
    Date of Patent: April 16, 2019
    Assignee: Intel Corporation
    Inventors: Saurabh Sharma, Abhishek Venkatesh, Travis T. Schluessler, Prasoonkumar Surti, Altug Koker, Aravindh V. Anantaraman, Pattabhiraman P. K., Abhishek R. Appu, Joydeep Ray, Kamal Sinha, Vasanth Ranganathan, Bhushan M. Borole, Wenyin Fu, Eric J. Hoekstra, Linda L. Hurd
  • Patent number: 10255656
    Abstract: An apparatus to facilitate compute optimization is disclosed. The apparatus includes sorting logic to sort processing threads into thread groups based on bit depth of floating point thread operations.
    Type: Grant
    Filed: October 31, 2017
    Date of Patent: April 9, 2019
    Assignee: INTEL CORPORATION
    Inventors: Abhishek R. Appu, Altug Koker, Linda L. Hurd, Dukhwan Kim, Mike B. Macpherson, John C. Weast, Feng Chen, Farshad Akhbari, Narayan Srinivasa, Nadathur Rajagopalan Satish, Joydeep Ray, Ping T. Tang, Michael S. Strickland, Xiaoming Chen, Anbang Yao, Tatiana Shpeisman
  • Publication number: 20190095703
    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.
    Type: Application
    Filed: September 6, 2018
    Publication date: March 28, 2019
    Applicant: Intel Corporation
    Inventors: Barnan Das, Mayuresh M. Varerkar, Narayan Biswal, Stanley J. Baran, Gokcen Cilingir, Nilesh V. Shah, Archie Sharma, Sherine Abdelhak, Praneetha Kotha, Neelay Pandit, John C. Weast, Mike B. Macpherson, Dukhwan Kim, Linda L. Hurd, Abhishek R. Appu, Altug Koker, Joydeep Ray
  • Patent number: 10242423
    Abstract: One embodiment provides an accelerator module comprising a memory stack including multiple memory dies; a graphics processing unit (GPU) coupled with the memory stack via one or more memory controllers, the GPU including a plurality of multiprocessors having a single instruction, multiple thread (SIMT) architecture, the multiprocessors to execute at least one single instruction; the at least one single instruction to cause at least a portion of the GPU to perform a floating-point operation on input having differing precisions; and the floating-point operation is a two-dimensional matrix multiply and accumulate operation.
    Type: Grant
    Filed: October 20, 2017
    Date of Patent: March 26, 2019
    Assignee: Intel Corporation
    Inventors: Elmoustapha Ould-Ahmed-Vall, Sara S. Baghsorkhi, Anbang Yao, Kevin Nealis, Xiaoming Chen, Altug Koker, Abhishek R. Appu, John C. Weast, Mike B. Macpherson, Dukhwan Kim, Linda L. Hurd, Ben J. Ashbaugh, Barath Lakshmanan, Liwei Ma, Joydeep Ray, Ping T. Tang, Michael S. Strickland
  • Publication number: 20190049982
    Abstract: Apparatuses, methods, and systems associated with safety-related decision making reporting and regulation of computer-assisted or autonomous driving (CA/AD) vehicles are disclosed herein. In some embodiments, an apparatus includes a safety-related decision making reporting unit, disposed in a CA/AD vehicle, to collect data about driving behavior of the CA/AD vehicle and to determine whether the collected data is related to a safety-related decision making rule. In embodiments, the collected data is to be reported to a remote organization associated with regulating the safety-related decision making rule. In some embodiments, a computing device or server associated with regulating safety-related decision making rules receives the collected data from the CA/AD vehicle and/or manufacturers of the CA/AD vehicle. In embodiments, the computing device analyzes the collected data to modify or generate a safety-decision making rule. Other embodiments are also described and claimed.
    Type: Application
    Filed: September 28, 2018
    Publication date: February 14, 2019
    Inventors: XUE YANG, SHERRY CHANG, CHAITANYA SREERAMA, LINDA L. HURD, DENICA LARSEN
  • Publication number: 20180314249
    Abstract: A mechanism is described for facilitating storage management for machine learning at autonomous machines. A method of embodiments, as described herein, includes detecting one or more components associated with machine learning, where the one or more components include memory and a processor coupled to the memory, and where the processor includes a graphics processor. The method may further include allocating a storage portion of the memory and a hardware portion of the processor to a machine learning training set, where the storage and hardware portions are precise for implementation and processing of the training set.
    Type: Application
    Filed: April 28, 2017
    Publication date: November 1, 2018
    Applicant: Intel Corporation
    Inventors: Abhishek R. Appu, John C. Weast, Sara S. Baghsorkhi, Justin E. Gottschlich, Prasoonkumar Surti, Chandrasekaran Sakthivel, Altug Koker, Farshad Akhbari, Feng Chen, Dukhwan Kim, Narayan Srinivasa, Nadathur Rajagopalan Satish, Kamal Sinha, Joydeep Ray, Balaji Vembu, Mike B. Macpherson, Linda L. Hurd, Sanjeev Jahagirdar, Vasanth Ranganathan
  • Publication number: 20180315159
    Abstract: One embodiment provides an accelerator module comprising a memory stack including multiple memory dies; a graphics processing unit (GPU) coupled with the memory stack via one or more memory controllers, the GPU including a plurality of multiprocessors having a single instruction, multiple thread (SIMT) architecture, the multiprocessors to execute at least one single instruction; the at least one single instruction to cause at least a portion of the GPU to perform a floating-point operation on input having differing precisions; and the floating-point operation is a two-dimensional matrix multiply and accumulate operation.
    Type: Application
    Filed: October 20, 2017
    Publication date: November 1, 2018
    Applicant: Intel Corporation
    Inventors: Elmoustapha Ould-Ahmed-Vall, Sara S. Baghsorkhi, Anbang Yao, Kevin Nealis, Xiaoming Chen, Altug Koker, Abhishek R. Appu, John C. Weast, Mike B. Macpherson, Dukhwan Kim, Linda L. Hurd, Ben J. Ashbaugh, Barath Lakshmanan, Liwei Ma, Joydeep Ray, Ping T. Tang, Michael S. Strickland
  • Publication number: 20180315157
    Abstract: One embodiment provides a general-purpose graphics processing unit comprising a dynamic precision floating-point unit including a control unit having precision tracking hardware logic to track an available number of bits of precision for computed data relative to a target precision, wherein the dynamic precision floating-point unit includes computational logic to output data at multiple precisions.
    Type: Application
    Filed: April 28, 2017
    Publication date: November 1, 2018
    Applicant: Intel Corporation
    Inventors: Elmoustapha Ould-Ahmed-Vall, Sara S. Baghsorkhi, Anbang Yao, Kevin Nealis, Xiaoming Chen, Altug Koker, Abhishek R. Appu, John C. Weast, Mike B. Macpherson, Dukhwan Kim, Linda L. Hurd, Ben . Ashbaugh, Barath Lakshmanan, Liwei Ma, Joydeep Ray, Ping T. Tang, Michael S. Strickland
  • Publication number: 20180308202
    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.
    Type: Application
    Filed: April 24, 2017
    Publication date: October 25, 2018
    Applicant: Intel Corporation
    Inventors: Abhishek R. Appu, Altug Koker, John C. Weast, Mike B. Macpherson, Linda L. Hurd, Sara S. Baghsorkhi, Justin E. Gottschlich, Prasoonkumar Surti, Chandrasekaran Sakthivel, Liwei Ma, Elmoustapha Ould-Ahmed-Vall, Kamal Sinha, Joydeep Ray, Balaji Vembu, Sanjeev Jahagirdar, Vasanth Ranganathan, DUKHWAN Kim
  • Publication number: 20180307983
    Abstract: An apparatus to facilitate optimization of a neural network (NN) is disclosed. The apparatus includes optimization logic to define a NN topology having one or more macro layers, adjust the one or more macro layers to adapt to input and output components of the NN and train the NN based on the one or more macro layers.
    Type: Application
    Filed: April 24, 2017
    Publication date: October 25, 2018
    Applicant: Intel Corporation
    Inventors: Narayan Srinivasa, Joydeep Ray, Nicolas C. Galoppo Von Borries, Ben Ashbaugh, Prasoonkumar Surti, Feng Chen, Barath Lakshmanan, Elmoustapha Ould-Ahmed-Vall, Liwei Ma, Linda L. Hurd, Abhishek R. Appu, John C. Weast, Sara S. Baghsorkhi, Justin E. Gottschlich, Chandrasekaran Sakthivel, Farshad Akhbari, Dukhwan Kim, Altug Koker, Nadathur Rajagopalan Satish
  • Publication number: 20180307494
    Abstract: One embodiment provides for a compute apparatus to perform machine learning operations, the compute apparatus comprising instruction decode logic to decode a single instruction including multiple operands into a single decoded instruction, the multiple operands having differing precisions and a general-purpose graphics compute unit including a first logic unit and a second logic unit, the general-purpose graphics compute unit to execute the single decoded instruction, wherein to execute the single decoded instruction includes to perform a first instruction operation on a first set of operands of the multiple operands at a first precision and a simultaneously perform second instruction operation on a second set of operands of the multiple operands at a second precision.
    Type: Application
    Filed: April 24, 2017
    Publication date: October 25, 2018
    Applicant: Intel Corporation
    Inventors: ELMOUSTAPHA OULD-AHMED-VALL, BARATH LAKSHMANAN, TATIANA SHPEISMAN, Joydeep Ray, Ping T. Tang, Michael Strickland, Xiaoming Chen, Anbang Yao, Ben J. Ashbaugh, Linda L. Hurd, Liwei Ma
  • Publication number: 20180308200
    Abstract: An apparatus to facilitate compute optimization is disclosed.
    Type: Application
    Filed: April 24, 2017
    Publication date: October 25, 2018
    Inventors: Prasoonkumar Surti, Narayan Srinivasa, Feng Chen, Joydeep Ray, Ben J. Ashbaugh, Nicolas C. Galoppo Von Borries, Eriko Nurvitadhi, Balaji Vembu, Tsung-Han Lin, Kamal Sinha, Rajkishore Barik, Sara S. Baghsorkhi, Justin E. Gottschlich, Altug Koker, Nadathur Rajagopalan Satish, Farshad Akhbari, Dukhwan Kim, Wenyin Fu, Travis T. Schluessler, Josh B. Mastronarde, Linda L. Hurd, John H. Feit, Jeffery S. Boles, Adam T. Lake, Karthik Vaidyanathan, Devan Burke, Subramaniam Maiyuran, Abhishek R. Appu
  • Publication number: 20180308272
    Abstract: Briefly, in accordance with one or more embodiments, a processor receives an incoming data stream that includes alpha channel data, and a memory stores an application programming interface (API). The API is to route the alpha channel data to a fixed point blending unit to perform one or more blending operations using fixed point representation of the alpha channel data. The API is further to route the incoming data stream to a floating point blending unit to perform operations involving floating point representation of the incoming data.
    Type: Application
    Filed: April 21, 2017
    Publication date: October 25, 2018
    Inventors: Abhishek R. Appu, Prasoonkumar Surti, Srivallaba Mysore, Subhajit Dasgupta, Hiroshi Akiba, Eric J. Hoekstra, Linda L. Hurd, Travis T. Schluessler, Daren J. Schmidt
  • Publication number: 20180307899
    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.
    Type: Application
    Filed: April 24, 2017
    Publication date: October 25, 2018
    Applicant: Intel Corproation
    Inventors: Barnan Das, MAYURESH M. VARERKAR, NARAYAN BISWAL, STANLEY J. BARAN, GOKCEN CILINGIR, NILESH V. SHAH, ARCHIE SHARMA, SHERINE ABDELHAK, Praneetha Kotha, Neelay Pandit, John C. Weast, Mike B. Macpherson, Dukhwan Kim, Linda L. Hurd, Abhishek R. Appu, Altug Koker, Joydeep Ray
  • Publication number: 20180307971
    Abstract: In an example, an apparatus comprises a compute engine comprising a high precision component and a low precision component; and logic, at least partially including hardware logic, to receive instructions in the compute engine; select at least one of the high precision component or the low precision component to execute the instructions; and apply a gate to at least one of the high precision component or the low precision component to execute the instructions. Other embodiments are also disclosed and claimed.
    Type: Application
    Filed: April 24, 2017
    Publication date: October 25, 2018
    Applicant: Intel Corpoartion
    Inventors: Kamal Sinha, Balaji Vembu, Eriko Nurvitadhi, Nicolas C. Galoppo Von Borries, Rajkishore Barik, Tsung-Han Lin, Joydeep Ray, Ping T. Tang, Michael S. Strickland, Xiaoming Chen, Anbang Yao, Tatiana Shpeisman, Abhishek R. Appu, Altug Koker, Farshad Akhbari, Narayan Srinivasa, Feng Chen, Dukhwan Kim, Nadathur Rajagopalan Satish, John C. Weast, Mike B. MacPherson, Linda L. Hurd, Vasanth Ranganathan, Sanjeev S. Jahagirdar
  • Publication number: 20180307985
    Abstract: A mechanism is described for facilitating barriers and synchronization for machine learning at autonomous machines. A method of embodiments, as described herein, includes detecting thread groups relating to machine learning associated with one or more processing devices. The method may further include facilitating barrier synchronization of the thread groups across multiple dies such that each thread in a thread group is scheduled across a set of compute elements associated with the multiple dies, where each die represents a processing device of the one or more processing devices, the processing device including a graphics processor.
    Type: Application
    Filed: April 24, 2017
    Publication date: October 25, 2018
    Applicant: Intel Corporation
    Inventors: Abhishek R. Appu, Altug Koker, Joydeep Ray, Balaji Vembu, John C. Weast, Mike B. Macpherson, Dukhwan Kim, Linda L. Hurd, Sanjeev Jahagirdar, Vasanth Ranganathan
  • Publication number: 20180307495
    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 (SIMT) architecture, the general-purpose graphics compute unit to simultaneously execute the first instruction and the second instruction, wherein the integer operation corresponds to a memory address calculation.
    Type: Application
    Filed: November 21, 2017
    Publication date: October 25, 2018
    Applicant: Intel Corporation
    Inventors: ELMOUSTAPHA OULD-AHMED-VALL, BARATH LAKSHMANAN, TATIANA SHPEISMAN, Joydeep Ray, Ping T. Tang, Michael Strickland, Xiaoming Chen, Anbang Yao, Ben J. Ashbaugh, Linda L. Hurd, Liwei Ma
  • Publication number: 20180308201
    Abstract: An apparatus to facilitate compute optimization is disclosed. The apparatus includes sorting logic to sort processing threads into thread groups based on bit depth of floating point thread operations.
    Type: Application
    Filed: April 24, 2017
    Publication date: October 25, 2018
    Inventors: Abhishek R. Appu, Altug Koker, Linda L. Hurd, Dukhwan Kim, Mike B. Macpherson, John C. Weast, Feng Chen, Farshad Akhbari, Narayan Srinivasa, Nadathur Rajagopalan Satish, Joydeep Ray, Ping T. Tang, Michael S. Strickland, Xiaoming Chen, Anbang Yao, Tatiana Shpeisman
  • Publication number: 20180308207
    Abstract: An apparatus to facilitate compute optimization is disclosed. The apparatus includes sorting logic to sort processing threads into thread groups based on bit depth of floating point thread operations.
    Type: Application
    Filed: October 31, 2017
    Publication date: October 25, 2018
    Applicant: Intel Corporation
    Inventors: Abhishek R. Appu, Altug Koker, Linda L. Hurd, Dukhwan Kim, Mike B. Macpherson, John C. Weast, Feng Chen, Farshad Akhbari, Narayan Srinivasa, Nadathur Rajagopalan Satish, Joydeep Ray, Ping T. Tang, Michael S. Strickland, Xiaoming Chen, Anbang Yao, Tatiana Shpeisman