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).
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Publication number: 20240086683Abstract: An apparatus to facilitate workload scheduling is disclosed. The apparatus includes one or more clients, one or more processing units to processes workloads received from the one or more clients, including hardware resources and scheduling logic to schedule direct access of the hardware resources to the one or more clients to process the workloads.Type: ApplicationFiled: September 21, 2023Publication date: March 14, 2024Applicant: Intel CorporationInventors: Liwei Ma, Nadathur Rajagopalan Satish, Jeremy Bottleson, Farshad Akhbari, Eriko Nurvitadhi, Chandrasekaran Sakthivel, Barath Lakshmanan, Jingyi Jin, Justin E. Gottschlich, Michael Strickland
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Publication number: 20240070926Abstract: 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: ApplicationFiled: September 13, 2023Publication date: February 29, 2024Applicant: Intel CorporationInventors: 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
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Publication number: 20240013337Abstract: A mechanism is described for detecting, at training time, information related to one or more tasks to be performed by the one or more processors according to a training dataset for a neural network, analyzing the information to determine one or more portions of hardware of a processor of the one or more processors that is configurable to support the one or more tasks, 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, and monitoring utilization of the hardware via a hardware unit of the graphics processor and, via a scheduler of the graphics processor, adjusting allocation of the one or more tasks to the one or more portions of the hardware based on the utilization.Type: ApplicationFiled: July 13, 2023Publication date: January 11, 2024Applicant: Intel CorporationInventors: 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
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Patent number: 11829525Abstract: 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.Type: GrantFiled: April 19, 2021Date of Patent: November 28, 2023Assignee: Intel CorporationInventors: Altug Koker, Michael Apodaca, Kai Xiao, Chandrasekaran Sakthivel, Jeffery S. Boles, Adam T. Lake, James M. Holland, Pattabhiraman K, Sayan Lahiri, Radhakrishnan Venkataraman, Kamal Sinha, Ankur N. Shah, Deepak S. Vembar, Abhishek R. Appu, Joydeep Ray, Elmoustapha Ould-Ahmed-Vall
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Publication number: 20230376762Abstract: Embodiments described herein provide an apparatus comprising an interconnect switch configured to couple with a plurality of graphics processors via a plurality of point-to-point interconnects and one or more processors including a graphics processor coupled with the interconnect switch via a point-to-point interconnect of the plurality of point-to-point interconnects.Type: ApplicationFiled: May 19, 2023Publication date: November 23, 2023Applicant: Intel CorporationInventors: Srinivas Sridharan, Karthikeyan Vaidyanathan, Dipankar Das, Chandrasekaran Sakthivel, Mikhail E. Smorkalov
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Patent number: 11810405Abstract: An autonomous vehicle is provided that includes one or more processors configured to provide a local compute manager to manage execution of compute workloads associated with the autonomous vehicle. The local compute manager can perform various compute operations, including receiving offload of compute operations from to other compute nodes and offloading compute operations to other compute notes, where the other compute nodes can be other autonomous vehicles. The local compute manager can also facilitate autonomous navigation functionality.Type: GrantFiled: November 30, 2021Date of Patent: November 7, 2023Assignee: Intel CorporationInventors: 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
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Patent number: 11809978Abstract: An apparatus to facilitate workload scheduling is disclosed. The apparatus includes one or more clients, one or more processing units to processes workloads received from the one or more clients, including hardware resources and scheduling logic to schedule direct access of the hardware resources to the one or more clients to process the workloads.Type: GrantFiled: April 18, 2022Date of Patent: November 7, 2023Assignee: Intel CorporationInventors: Liwei Ma, Nadathur Rajagopalan Satish, Jeremy Bottleson, Farshad Akhbari, Eriko Nurvitadhi, Chandrasekaran Sakthivel, Barath Lakshmanan, Jingyi Jin, Justin E. Gottschlich, Michael Strickland
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Patent number: 11797837Abstract: 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: GrantFiled: April 24, 2017Date of Patent: October 24, 2023Assignee: Intel CorporationInventors: 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
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Patent number: 11798198Abstract: 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: GrantFiled: January 10, 2023Date of Patent: October 24, 2023Assignee: INTEL CORPORATIONInventors: 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
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Publication number: 20230334316Abstract: Described herein is a graphics processor comprising a memory device and a graphics processing cluster coupled with the memory device. The graphics processing cluster includes a plurality of graphics multiprocessors interconnected via a data interconnect. A graphics multiprocessor includes circuitry configured to load a modular neural network including a plurality of subnetworks, each of the plurality of subnetworks trained to perform a computer vision operation on a separate subject.Type: ApplicationFiled: May 9, 2023Publication date: October 19, 2023Applicant: Intel CorporationInventors: 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
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Patent number: 11756247Abstract: 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.Type: GrantFiled: March 8, 2021Date of Patent: September 12, 2023Assignee: Intel CorporationInventors: Deepak S. Vembar, Atsuo Kuwahara, Chandrasekaran Sakthivel, Radhakrishnan Venkataraman, Brent E. Insko, Anupreet S. Kalra, Hugues Labbe, Abhishek R. Appu, Ankur N. Shah, Joydeep Ray, ElMoustapha Ould-Ahmed-Vall, James M. Holland
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Patent number: 11748841Abstract: A mechanism is described for facilitating inference coordination and processing utilization for machine learning. A method of embodiments, as described herein, includes limiting execution of workloads for the respective contexts of a plurality of contexts to a specified subset of a plurality of processing resources of a processing system according to physical resource slices of the processing system that are associated with the respective contexts of the plurality of contexts.Type: GrantFiled: July 22, 2022Date of Patent: September 5, 2023Assignee: Intel CorporationInventors: 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
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Publication number: 20230230289Abstract: 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: ApplicationFiled: January 10, 2023Publication date: July 20, 2023Applicant: Intel CorporationInventors: 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
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Patent number: 11704565Abstract: 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 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. The processor can transparently adjust communication paths between worker nodes based on the communication pattern.Type: GrantFiled: March 3, 2022Date of Patent: July 18, 2023Assignee: Intel CorporationInventors: Srinivas Sridharan, Karthikeyan Vaidyanathan, Dipankar Das, Chandrasekaran Sakthivel, Mikhail E. Smorkalov
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Patent number: 11669932Abstract: 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: GrantFiled: June 23, 2021Date of Patent: June 6, 2023Assignee: INTEL CORPORATIONInventors: 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
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Patent number: 11609856Abstract: 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: GrantFiled: March 19, 2021Date of Patent: March 21, 2023Assignee: INTEL CORPORATIONInventors: 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
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Patent number: 11592817Abstract: 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: GrantFiled: April 28, 2017Date of Patent: February 28, 2023Assignee: INTEL CORPORATIONInventors: 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
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Patent number: 11580361Abstract: 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: GrantFiled: April 24, 2017Date of Patent: February 14, 2023Assignee: Intel CorporationInventors: Gokcen Cilingir, Elmoustapha Ould-Ahmed-Vall, Rajkishore Barik, Kevin Nealis, Xiaoming Chen, Justin E. Gottschlich, Prasoonkumar Surti, Chandrasekaran Sakthivel, Abhishek Appu, John C. Weast, Sara S. Baghsorkhi, Barnan Das, Narayan Biswal, Stanley J. Baran, Nilesh V. Shah, Archie Sharma, Mayuresh M. Varerkar
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Publication number: 20230039729Abstract: 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: ApplicationFiled: October 11, 2022Publication date: February 9, 2023Applicant: Intel CorporationInventors: 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
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Patent number: 11557064Abstract: 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: GrantFiled: January 23, 2020Date of Patent: January 17, 2023Inventors: 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