Patents by Inventor Mike B. MacPherson

Mike B. MacPherson 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: 20190146915
    Abstract: Embodiments of techniques and systems for execution of code with multiple page tables are described. In embodiments, a heterogenous system utilizing multiple processors may use multiple page tables to selectively execute appropriate ones of different versions of executable code. The system may be configured to support use of function pointers to virtual memory addresses. In embodiments, a virtual memory address may be mapped, such as during a code fetch. In embodiments, when a processor seeks to perform a code fetch using the function pointer, a page table associated with the processor may be used to translate the virtual memory address to a physical memory address where code executable by the processor may be found. Usage of multiple page tables may allow the system to support function pointers while utilizing only one virtual memory address for each function that is pointed to. Other embodiments may be described and claimed.
    Type: Application
    Filed: December 4, 2018
    Publication date: May 16, 2019
    Inventor: Mike B. MacPherson
  • 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
  • Patent number: 10146687
    Abstract: Embodiments of techniques and systems for execution of code with multiple page tables are described. In embodiments, a heterogenous system utilizing multiple processors may use multiple page tables to selectively execute appropriate ones of different versions of executable code. The system may be configured to support use of function pointers to virtual memory addresses. In embodiments, a virtual memory address may be mapped, such as during a code fetch. In embodiments, when a processor seeks to perform a code fetch using the function pointer, a page table associated with the processor may be used to translate the virtual memory address to a physical memory address where code executable by the processor may be found. Usage of multiple page tables may allow the system to support function pointers while utilizing only one virtual memory address for each function that is pointed to. Other embodiments may be described and claimed.
    Type: Grant
    Filed: April 25, 2017
    Date of Patent: December 4, 2018
    Assignee: Intel Corporation
    Inventor: Mike B. Macpherson
  • 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: 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: 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: 20180314250
    Abstract: A mechanism is described for facilitating smart collection of data and smart management of autonomous machines. A method of embodiments, as described herein, includes detecting one or more sets of data from one or more sources over one or more networks, and combining a first computation directed to be performed locally at a local computing device with a second computation directed to be performed remotely at a remote computing device in communication with the local computing device over the one or more networks, where the first computation consumes low power, wherein the second computation consumes high power.
    Type: Application
    Filed: April 28, 2017
    Publication date: November 1, 2018
    Applicant: Intel Corporation
    Inventors: Brian T. Lewis, Feng Chen, Jeffrey R. Jackson, Justin E. Gottschlich, Rajkishore Barik, Xiaoming Chen, Prasoonkumar Surti, Mike B. Macpherson, Murali Sundaresan
  • 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: 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: 20180308203
    Abstract: A mechanism is described for facilitating sharing of data and compression expansion of models at autonomous machines. A method of embodiments, as described herein, includes detecting a first processor processing information relating to a neural network at a first computing device, where the first processor comprises a first graphics processor and the first computing device comprises a first autonomous machine. The method further includes facilitating the first processor to store one or more portions of the information in a library at a database, where the one or more portions are accessible to a second processor of a computing device.
    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, Dukhwan Kim, Linda L. Hurd, Sara S. Baghsorkhi, Justin E. Gottschlich, Prasoonkumar Surti, Chandrasekaran Sakthivel, Joydeep Ray
  • 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
  • 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: 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
  • Patent number: 10108850
    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: Grant
    Filed: April 24, 2017
    Date of Patent: October 23, 2018
    Assignee: 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
  • Publication number: 20180299841
    Abstract: Methods and apparatus relating to autonomous vehicle neural network optimization techniques are described. In an embodiment, the difference between a first training dataset to be used for a neural network and a second training dataset to be used for the neural network is detected. The second training dataset is authenticated in response to the detection of the difference. The neural network is used to assist in an autonomous vehicle/driving. Other embodiments are also disclosed and claimed.
    Type: Application
    Filed: April 17, 2017
    Publication date: October 18, 2018
    Applicant: Intel Corporation
    Inventors: Abhishek R. Appu, Altug Koker, Linda L. Hurd, Dukhwan Kim, Mike B. MacPherson, John C. Weast, Justin E. Gottschlich, Jingyi Jin, Barath Lakshmanan, Chandrasekaran Sakthivel, Michael S. Strickland, Joydeep Ray, Kamal Sinha, Prasoonkumar Surti, Balaji Vembu, Ping T. Tang, Anbang Yao, Tatiana Shpeisman, Xiaoming Chen, Vasanth Ranganathan, Sanjeev S. Jahagirdar
  • Publication number: 20180300600
    Abstract: An apparatus to facilitate optimization of a convolutional neural network (CNN) is disclosed. The apparatus includes optimization logic to receive a CNN model having a list of instructions and including pruning logic to optimize the list of instructions by eliminating branches in the list of instructions that comprise a weight value of 0.
    Type: Application
    Filed: April 17, 2017
    Publication date: October 18, 2018
    Applicant: Intel Corporation
    Inventors: Liwei Ma, Elmoustapha Ould- Ahmed-Vall, Barath Lakshmanan, Ben J. Ashbaugh, Jingyi Jin, Jeremy Bottleson, Mike B. Macpherson, Kevin Nealis, Dhawal Srivastava, Joydeep Ray, Ping T. Tang, Michael S. Strickland, Xiaoming Chen, Anbang Yao, Tatiana Shpeisman, Altug Koker, Abhishek R. Appu
  • Publication number: 20170228315
    Abstract: Embodiments of techniques and systems for execution of code with multiple page tables are described. In embodiments, a heterogenous system utilizing multiple processors may use multiple page tables to selectively execute appropriate ones of different versions of executable code. The system may be configured to support use of function pointers to virtual memory addresses. In embodiments, a virtual memory address may be mapped, such as during a code fetch. In embodiments, when a processor seeks to perform a code fetch using the function pointer, a page table associated with the processor may be used to translate the virtual memory address to a physical memory address where code executable by the processor may be found. Usage of multiple page tables may allow the system to support function pointers while utilizing only one virtual memory address for each function that is pointed to. Other embodiments may be described and claimed.
    Type: Application
    Filed: April 25, 2017
    Publication date: August 10, 2017
    Inventor: Mike B. Macpherson