Patents by Inventor Chandrasekaran Sakthivel

Chandrasekaran Sakthivel 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: 20190206090
    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.
    Type: Application
    Filed: December 30, 2017
    Publication date: July 4, 2019
    Applicant: Intel Corporation
    Inventors: 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
  • Publication number: 20190205745
    Abstract: Embodiments described herein provide a system to configure distributed training of a neural network, the system comprising memory to store a library to facilitate data transmission during distributed training of the neural network; a network interface to enable transmission and receipt of configuration data associated with a set of worker nodes, the worker nodes configured to perform distributed training of the neural network; and a processor to execute instructions provided by the library, the instructions to cause the processor to create one or more groups of the worker nodes, the one or more groups of worker nodes to be created based on a communication pattern for messages to be transmitted between the worker nodes during distributed training of the neural network.
    Type: Application
    Filed: December 29, 2017
    Publication date: July 4, 2019
    Applicant: Intel Corporation
    Inventors: Srinivas Sridharan, Karthikeyan Vaidyanathan, Dipankar Das, Chandrasekaran Sakthivel, Mikhail E. Smorkalov
  • Patent number: 10332320
    Abstract: One embodiment provides for a computing device within an autonomous vehicle, the compute device comprising a wireless network device to enable a wireless data connection with an autonomous vehicle network, a set of multiple processors including a general-purpose processor and a general-purpose graphics processor, the set of multiple processors to execute a compute manager to manage execution of compute workloads associated with the autonomous vehicle, the compute workload associated with autonomous operations of the autonomous vehicle, and offload logic configured to execute on the set of multiple processors, the offload logic to determine to offload one or more of the compute workloads to one or more autonomous vehicles within range of the wireless network device.
    Type: Grant
    Filed: April 17, 2017
    Date of Patent: June 25, 2019
    Assignee: Intel Corporation
    Inventors: Barath Lakshamanan, Linda L. Hurd, Ben J. Ashbaugh, Elmoustapha Ould-Ahmed-Vall, Liwei Ma, Jingyi Jin, Justin E. Gottschlich, Chandrasekaran Sakthivel, Michael S. Strickland, Brian T. Lewis, Lindsey Kuper, Altug Koker, Abhishek R. Appu, Prasoonkumar Surti, Joydeep Ray, Balaji Vembu, Javier S. Turek, Naila Farooqui
  • Publication number: 20190180494
    Abstract: 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.
    Type: Application
    Filed: December 28, 2018
    Publication date: June 13, 2019
    Inventors: Atsuo Kuwahara, Deepak S. Vembar, Chandrasekaran Sakthivel, Radhakrishnan Venkataraman, Brent E. Insko, Anupreet S. Kalra, Hugues Labbe, Abhishek R. Appu, Ankur N. Shah, Joydeep Ray, Elmoustapha Ould-Ahmed-Vall, Prasoonkumar Surti, Murali Ramadoss
  • Patent number: 10304154
    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: Grant
    Filed: April 24, 2017
    Date of Patent: May 28, 2019
    Assignee: 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
  • Patent number: 10297002
    Abstract: An apparatus and method are described for using a touch screen device to control an external display. For example, one embodiment of an apparatus comprises a touch screen to receive user touch input and display images; a processor communicatively coupled to the touch screen; a wireless session management module to establish and maintain a wireless display connection with an extended screen responsive to commands from the processor; and the processor to execute a process responsive to the user touch input to transform the touch screen or a portion thereof to a remote control touchpad device usable to provide control functions for content displayed on the extended screen.
    Type: Grant
    Filed: March 10, 2015
    Date of Patent: May 21, 2019
    Assignee: Intel Corporation
    Inventors: Tri T. Khuong, Chandrasekaran Sakthivel, Kamalakar V. Pawar
  • Patent number: 10261903
    Abstract: In an example, an apparatus comprises a plurality of processing unit cores, a plurality of cache memory modules associated with the plurality of processing unit cores, and a machine learning model communicatively coupled to the plurality of processing unit cores, wherein the plurality of cache memory modules share cache coherency data with the machine learning model. Other embodiments are also disclosed and claimed.
    Type: Grant
    Filed: April 17, 2017
    Date of Patent: April 16, 2019
    Assignee: INTEL CORPORATION
    Inventors: Chandrasekaran Sakthivel, Prasoonkumar Surti, John C. Weast, Sara S. Baghsorkhi, Justin E. Gottschlich, Abhishek R. Appu, Nicolas C. Galoppo Von Borries, Joydeep Ray, Narayan Srinivasa, Feng Chen, Ben J. Ashbaugh, Rajkishore Barik, Tsung-Han Lin, Kamal Sinha, Eriko Nurvitadhi, Balaji Vembu, Altug Koker
  • Patent number: 10242486
    Abstract: Systems, apparatuses and methods may provide away to render augmented reality and virtual reality (VR/AR) environment information. More particularly, systems, apparatuses and methods may provide a way to selectively suppress and enhance VR/AR renderings of n-dimensional environments. The systems, apparatuses and methods may deepen a user's VR/AR experience by focusing on particular feedback information, while suppressing other feedback information from the environment.
    Type: Grant
    Filed: April 17, 2017
    Date of Patent: March 26, 2019
    Assignee: Intel Corporation
    Inventors: Chandrasekaran Sakthivel, Michael Apodaca, Kai Xiao, Altug Koker, Jeffery S. Boles, Adam T. Lake, Nikos Kaburlasos, Joydeep Ray, John H. Feit, Travis T. Schluessler, Jacek Kwiatkowski, James M. Holland, Prasoonkumar Surti, Jonathan Kennedy, Louis Feng, Barnan Das, Narayan Biswal, Stanley J. Baran, Gokcen Cilingir, Nilesh V. Shah, Archie Sharma, Mayuresh M. Varerkar
  • Publication number: 20190073514
    Abstract: Systems, apparatuses, and methods may provide for technology to dynamically control a display in response to ocular characteristic measurements of at least one eye of a user.
    Type: Application
    Filed: November 6, 2018
    Publication date: March 7, 2019
    Inventors: Radhakrishnan Venkataraman, James M. Holland, Sayan Lahiri, Pattabhiraman K, Kamal Sinha, Chandrasekaran Sakthivel, Daniel Pohl, Vivek Tiwari, Philip R. Laws, Subramaniam Maiyuran, Abhishek R. Appu, ElMoustapha Ould-Ahmed-Vall, Peter L. Doyle, Devan Burke
  • Patent number: 10152632
    Abstract: Systems, apparatuses, and methods may provide for technology to dynamically control a display in response to ocular characteristic measurements of at least one eye of a user.
    Type: Grant
    Filed: April 10, 2017
    Date of Patent: December 11, 2018
    Assignee: Intel Corporation
    Inventors: Radhakrishnan Venkataraman, James M. Holland, Sayan Lahiri, Pattabhiraman K, Kamal Sinha, Chandrasekaran Sakthivel, Daniel Pohl, Vivek Tiwari, Philip R. Laws, Subramaniam Maiyuran, Abhishek R. Appu, ElMoustapha Ould-Ahmed-Vall, Peter L. Doyle, Devan Burke
  • 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: 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: 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: 20180307981
    Abstract: An apparatus to facilitate neural network (NN) training is disclosed. The apparatus includes training logic to receive one or more network constraints and train the NN by automatically determining a best network layout and parameters based on the network constraints.
    Type: Application
    Filed: April 24, 2017
    Publication date: October 25, 2018
    Inventors: Gokcen Cilingir, Elmoustapha Ould-Ahmed-Vall, Rajkishore Barik, Kevin Nealis, Xiaoming Chen, Justin E. Gottschlich, Prasoonkumar Surti, Chandrasekaran Sakthivel, Abhishek R. Appu, John C. Weast, Sara S. Baghsorkhi, Barnan Das, Narayan Biswal, Stanley J. Baran, Nilesh Shah, Archie Sharma, Mayuresh M. Varerkar
  • Publication number: 20180307984
    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.
    Type: Application
    Filed: April 24, 2017
    Publication date: October 25, 2018
    Applicant: Intel Corporation
    Inventors: Altug Koker, Abhishek R. Appu, Kamal Sinha, Joydeep Ray, Balaji Vembu, Elmoustapha Ould-Ahmed-Vall, Sara S. Baghsorkhi, Anbang Yao, Kevin Nealis, Xiaoming Chen, John C. Weast, Justin E. Gottschlich, Prasoonkumar Surti, Chandrasekaran Sakthivel, Farshad Akhbari, Nadathur Rajagopalan Satish, Liwei Ma, Jeremy Bottleson, Eriko Nurvitadhi, Travis T. Schluessler, Ankur N. Shah, Jonathan Kennedy, Vasanth Ranganathan, Sanjeev Jahagirdar
  • Publication number: 20180300098
    Abstract: 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.
    Type: Application
    Filed: April 17, 2017
    Publication date: October 18, 2018
    Inventors: Deepak S. Vembar, Atsuo Kuwahara, Chandrasekaran Sakthivel, Radhakrishnan Venkataraman, Brent E. Insko, Anupreet S. Kalra, Hugues Labbe, Altug Koker, Michael Apodaca, Kai Xiao, Jeffery S. Boles, Adam T. Lake, David M. Cimini, Balaji Vembu, Elmoustapha Ould-Ahmed-Vall, Jacek Kwiatkowski, Philip R. Laws, Ankur N. Shah, Abhishek R. Appu, Joydeep Ray, Wenyin Fu, Nikos Kaburlasos, Prasoonkumar Surti, Bhushan M. Borole
  • 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: 20180300932
    Abstract: 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.
    Type: Application
    Filed: April 17, 2017
    Publication date: October 18, 2018
    Inventors: Atsuo Kuwahara, Deepak S. Vembar, Chandrasekaran Sakthivel, Radhakrishnan Venkataraman, Brent E. Insko, Anupreet S. Kalra, Hugues Labbe, Abhishek R. Appu, Ankur N. Shah, Joydeep Ray, Elmoustapha Ould-Ahmed-Vall, Prasoonkumar Surti, Murali Ramadoss
  • Publication number: 20180300246
    Abstract: In an example, an apparatus comprises a plurality of processing unit cores, a plurality of cache memory modules associated with the plurality of processing unit cores, and a machine learning model communicatively coupled to the plurality of processing unit cores, wherein the plurality of cache memory modules share cache coherency data with the machine learning model. Other embodiments are also disclosed and claimed.
    Type: Application
    Filed: April 17, 2017
    Publication date: October 18, 2018
    Applicant: Intel Corporation
    Inventors: Chandrasekaran Sakthivel, Prasoonkumar Surti, John C. Weast, Sara S. Baghsorkhi, Justin E. Gottschlich, Abhishek R. Appu, Nicolas C. Galoppo Von Borries, Joydeep Ray, Narayan Srinivasa, Feng Chen, Ben J. Ashbaugh, Rajkishore Barik, Tsung-Han Lin, Kamal Sinha, Eriko Nurvitadhi, Balaji Vembu, Altug Koker