Patents by Inventor Abhishek R. Appu
Abhishek R. Appu 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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Patent number: 11748302Abstract: In an example, an apparatus comprises a plurality of execution units, and a first memory communicatively couple to the plurality of execution units, wherein the first shared memory is shared by the plurality of execution units and a copy engine to copy context state data from at least a first of the plurality of execution units to the first shared memory. Other embodiments are also disclosed and claimed.Type: GrantFiled: December 23, 2021Date of Patent: September 5, 2023Assignee: INTEL CORPORATIONInventors: Altug Koker, Prasoonkumar Surti, David Puffer, Subramaniam Maiyuran, Guei-Yuan Lueh, Abhishek R. Appu, Joydeep Ray, Balaji Vembu, Tomer Bar-On, Andrew T. Lauritzen, Hugues Labbe, John G. Gierach, Gabor Liktor
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Patent number: 11748106Abstract: A mechanism is described for facilitating fast data operations and for facilitating a finite state machine for machine learning at autonomous machines. A method of embodiments, as described herein, includes detecting input data to be used in computational tasks by a computation component of a processor including a graphics processor. The method may further include determining one or more frequently-used data values (FDVs) from the data, and pushing the one or more frequent data values to bypass the computational tasks.Type: GrantFiled: March 1, 2022Date of Patent: September 5, 2023Assignee: INTEL CORPORATIONInventors: Liwei Ma, Nadathur Rajagopalan Satish, Jeremy Bottleson, Farshad Akhbari, Eriko Nurvitadhi, Abhishek R. Appu, Altug Koker, Kamal Sinha, Joydeep Ray, Balaji Vembu, Vasanth Ranganathan, Sanjeev Jahagirdar
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Patent number: 11733758Abstract: Methods and apparatus relating to techniques for avoiding cache lookup for cold cache. In an example, an apparatus comprises logic, at least partially comprising hardware logic, to collect user information for a user of a data processing device, generate a user profile for the user of the data processing device from the user information, and set a power profile a processor in the data processing device using the user profile. Other embodiments are also disclosed and claimed.Type: GrantFiled: August 25, 2021Date of Patent: August 22, 2023Assignee: INTEL CORPORATIONInventors: Altug Koker, Abhishek R. Appu, Kiran C. Veernapu, Joydeep Ray, Balaji Vembu, Prasoonkumar Surti, Kamal Sinha, Eric J. Hoekstra, Wenyin Fu, Nikos Kaburlasos, Bhushan M. Borole, Travis T. Schluessler, Ankur N. Shah, Jonathan Kennedy
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Publication number: 20230260072Abstract: Embodiments provide mechanisms to facilitate compute operations for deep neural networks. One embodiment comprises a graphics processing unit comprising one or more multiprocessors, at least one of the one or more multiprocessors including a register file to store a plurality of different types of operands and a plurality of processing cores. The plurality of processing cores includes a first set of processing cores of a first type and a second set of processing cores of a second type. The first set of processing cores are associated with a first memory channel and the second set of processing cores are associated with a second memory channel.Type: ApplicationFiled: February 13, 2023Publication date: August 17, 2023Applicant: Intel CorporationInventors: 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
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Publication number: 20230260075Abstract: Embodiments described herein are generally directed to improvements relating to power, latency, bandwidth and/or performance issues relating to GPU processing/caching. According to one embodiment, a state of multiple intellectual property (IP) cores that have access to a common cache via a central fabric is observed. Responsive to the observed state being indicative of performance of a standalone workload by a first IP core of the multiple IP cores, the common cache is treated as a local cache of the first IP core by powering off the central fabric and causing the first IP core to access the common cache via a low power access path between the first IP core and the common cache that is outside of the central fabric.Type: ApplicationFiled: April 24, 2023Publication date: August 17, 2023Applicant: Intel CorporationInventors: Subramaniam Maiyuran, Durgaprasad Bilagi, Joydeep Ray, Scott Janus, Sanjeev Jahagirdar, Brent Insko, Lidong Xu, Abhishek R. Appu, James Holland, Vasanth Ranganathan, Nikos Kaburlasos, Altug Koker, Xinmin Tian, Guei-Yuan Lueh, Changliang Wang
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Publication number: 20230259458Abstract: One embodiment provides circuitry coupled with cache memory and a memory interface, the circuitry to compress compute data at multiple cache line granularity, and a processing resource coupled with the memory interface and the cache memory. The processing resource is configured to perform a general-purpose compute operation on compute data associated with multiple cache lines of the cache memory. The circuitry is configured to compress the compute data before a write of the compute data via the memory interface to the memory bus, in association with a read of the compute data associated with the multiple cache lines via the memory interface, decompress the compute data, and provide the decompressed compute data to the processing resource.Type: ApplicationFiled: February 13, 2023Publication date: August 17, 2023Applicant: Intel CorporationInventors: Abhishek R. Appu, Altug Koker, Joydeep Ray, David Puffer, Prasoonkumar Surti, Lakshminarayanan Striramassarma, Vasanth Ranganathan, Kiran C. Veernapu, Balaji Vembu, Pattabhiraman K
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Patent number: 11727246Abstract: Embodiments provide systems and methods which facilitate optimization of a convolutional neural network (CNN). One embodiment provides for a non-transitory machine-readable medium storing instructions that cause one or more processors to perform operations comprising processing a trained convolutional neural network (CNN) to generate a processed CNN, the trained CNN having weights in a floating-point format. Processing the trained CNN includes quantizing the weights in the floating-point format to generate weights in an integer format. Quantizing the weights includes generating a quantization table to enable non-uniform quantization of the weights and quantizing the weights from the floating-point format to the integer format using the quantization table. The operations additionally comprise performing an inference operation utilizing the processed CNN with the integer format weights.Type: GrantFiled: February 22, 2019Date of Patent: August 15, 2023Assignee: Intel CorporationInventors: 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
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Patent number: 11726826Abstract: Examples are described here that can be used to allocate commands from multiple sources to performance by one or more segments of a processing device. For example, a processing device can be segmented into multiple portions and each portion is allocated to process commands from a particular source. In the event a single source provides commands, the entire processing device (all segments) can be allocated to process commands from the single source. When a second source provides commands, some segments can be allocated to perform commands from the first source and other segments can be allocated to perform commands from the second source. Accordingly, commands from multiple applications can be executed by a processing unit at the same time.Type: GrantFiled: June 4, 2021Date of Patent: August 15, 2023Assignee: Intel CorporationInventors: James Valerio, Vasanth Ranganathan, Joydeep Ray, Rahul A. Kulkarni, Abhishek R. Appu, Jeffery S. Boles, Hema C. Nalluri
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Patent number: 11726793Abstract: Embodiments described herein provide an apparatus comprising a plurality of processing resources including a first processing resource and a second processing resource, a memory communicatively coupled to the first processing resource and the second processing resource, and a processor to receive data dependencies for one or more tasks comprising one or more producer tasks executing on the first processing resource and one or more consumer tasks executing on the second processing resource and move a data output from one or more producer tasks executing on the first processing resource to a cache memory communicatively coupled to the second processing resource. Other embodiments may be described and claimed.Type: GrantFiled: November 11, 2020Date of Patent: August 15, 2023Assignee: INTEL CORPORATIONInventors: Christopher J. Hughes, Prasoonkumar Surti, Guei-Yuan Lueh, Adam T. Lake, Jill Boyce, Subramaniam Maiyuran, Lidong Xu, James M. Holland, Vasanth Ranganathan, Nikos Kaburlasos, Altug Koker, Abhishek R. Appu
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Publication number: 20230252010Abstract: Embodiments are generally directed to compression for compression for sparse data structures utilizing mode search approximation. An embodiment of an apparatus includes one or more processors including a graphics processor to process data; and a memory for storage of data, including compressed data. The one or more processors are to provide for compression of a data structure, including identification of a mode in the data structure, the data structure including a plurality of values and the mode being a most repeated value in a data structure, wherein identification of the mode includes application of a mode approximation operation, and encoding of an output vector to include the identified mode, a significance map to indicate locations at which the mode is present in the data structure, and remaining uncompressed data from the data structure.Type: ApplicationFiled: December 15, 2022Publication date: August 10, 2023Applicant: Intel CorporationInventors: Prasoonkumar Surti, Abhishek R. Appu, Karol Szerszen, Eric Liskay, Karthik Vaidyanathan
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Patent number: 11720355Abstract: One embodiment provides a graphics processor comprising a memory controller and a graphics processing resource coupled with the memory controller. The graphics processing resource includes circuitry configured to execute an instruction to perform a matrix operation on first input including weight data and second input including input activation data, generate intermediate data based on a result of the matrix operation, quantize the intermediate data to a floating-point format determined based on a statistical distribution of first output data, and output, as second output data, quantized intermediate data in a determined floating-point format.Type: GrantFiled: June 7, 2022Date of Patent: August 8, 2023Assignee: Intel CorporationInventors: Himanshu Kaul, Mark A. Anders, Sanu K. Mathew, Anbang Yao, Joydeep Ray, Ping T. Tang, Michael S. Strickland, Xiaoming Chen, Tatiana Shpeisman, Abhishek R. Appu, Altug Koker, Kamal Sinha, Balaji Vembu, Nicolas C. Galoppo Von Borries, Eriko Nurvitadhi, Rajkishore Barik, Tsung-Han Lin, Vasanth Ranganathan, Sanjeev Jahagirdar
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Publication number: 20230244610Abstract: One embodiment provides an apparatus comprising a memory device configured to store a page table that includes a set of page table entries and a graphics processing cluster array including a plurality of graphics multiprocessors, the plurality of graphics multiprocessors coupled via a data interconnect. The graphics multiprocessor of the plurality of graphics multiprocessors includes a translation lookaside buffer (TLB) coupled with the memory device, the TLB to cache a first page table entry of the set of page table entries, the first page table entry to indicate that a first virtual page is a valid page that is cleared to a clear color and circuitry to bypass an access to the memory device for the first virtual page and determine a color associated with the first virtual page based on the indication that the first virtual page is a valid page that is cleared to the clear color.Type: ApplicationFiled: April 10, 2023Publication date: August 3, 2023Applicant: Intel CorporationInventors: Prasoonkumar Surti, Abhishek R. Appu, Kiran C. Veernapu
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Patent number: 11715174Abstract: Embodiments described herein provide techniques enable a graphics processor to continue processing operations during the reset of a compute unit that has experienced a hardware fault. Threads and associated context state for a faulted compute unit can be migrated to another compute unit of the graphics processor and the faulting compute unit can be reset while processing operations continue.Type: GrantFiled: March 3, 2022Date of Patent: August 1, 2023Assignee: Intel CorporationInventors: Murali Ramadoss, Balaji Vembu, Eric C. Samson, Kun Tian, David J. Cowperthwaite, Altug Koker, Zhi Wang, Joydeep Ray, Subramaniam M. Maiyuran, Abhishek R. Appu
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Patent number: 11710267Abstract: Systems, apparatuses, and methods may provide for technology to process graphics data in a virtual gaming environment. The technology may identify, from graphics data in a graphics application, redundant graphics calculations relating to common frame characteristics of one or more graphical scenes to be shared between client game devices of a plurality of users and calculate, in response to the identified redundant graphics calculations, frame characteristics relating to the one or more graphical scenes. Additionally, the technology may send, over a computer network, the calculation of the frame characteristics to the client game devices.Type: GrantFiled: September 17, 2021Date of Patent: July 25, 2023Assignee: Intel CorporationInventors: Jonathan Kennedy, Gabor Liktor, Jeffery S. Boles, Slawomir Grajewski, Balaji Vembu, Travis T. Schluessler, Abhishek R. Appu, Ankur N. Shah, Joydeep Ray, Altug Koker, Jacek Kwiatkowski
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Patent number: 11699404Abstract: Often when there is a glare on a display screen the user may be able to mitigate the glare by tilting or otherwise moving the screen or changing their viewing position. However, when driving a car there are limited options for overcoming glares on the dashboard, especially when you are driving for a long distance in the same direction. Embodiments are directed to eliminating such glare. Other embodiments are related to mixed reality (MR) and filling in occluded areas.Type: GrantFiled: March 24, 2022Date of Patent: July 11, 2023Assignee: Intel CorporationInventors: Arthur J. Runyan, Richmond Hicks, Nausheen Ansari, Narayan Biswal, Ya-Ti Peng, Abhishek R. Appu, Wen-Fu Kao, Sang-Hee Lee, Joydeep Ray, Changliang Wang, Satyanarayana Avadhanam, Scott Janus, Gary Smith, Nilesh V. Shah, Keith W. Rowe, Robert J. Johnston
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Publication number: 20230215400Abstract: An embodiment of an electronic processing system may include an application processor, persistent storage media communicatively coupled to the application processor, a graphics subsystem communicatively coupled to the application processor, an object space adjuster communicatively coupled to the graphics subsystem to adjust an object space parameter based on a screen space parameter, and a sample adjuster communicatively coupled to the graphics subsystem to adjust a sample parameter of the graphics subsystem based on a detected condition. Other embodiments are disclosed and claimed.Type: ApplicationFiled: March 6, 2023Publication date: July 6, 2023Applicant: Intel CorporationInventors: Louis Feng, Altug Koker, Tomasz Janczak, Andrew T. Lauritzen, David M. Cimini, Nikos Kaburlasos, Joydeep Ray, John H. Feit, Travis T. Schluessler, Jacek Kwiatkowski, Philip R. Laws, Devan Burke, Elmoustapha Ould-Ahmed-Vall, Abhishek R. Appu
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Publication number: 20230205704Abstract: A graphics processor includes multiple levels of memory units, including a memory device and a cache device located near a graphics component. The graphics processor includes distributed compression/decompression, including a module between the cache device and the memory device. The module can perform compression of write data when the write data is moved from the cache device to the memory device, and perform decompression of read data when the read data is moved from the memory device to the cache device. The graphics processor can include a second level of cache with another compression module between the first level of cache and the second level of cache.Type: ApplicationFiled: December 23, 2021Publication date: June 29, 2023Inventors: Prasoonkumar SURTI, Vidhya KRISHNAN, Abhishek R. APPU, Karol A. SZERSZEN, Lakshminarayanan STRIRAMASSARMA
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Publication number: 20230205587Abstract: Thread group dispatch in a clustered graphics architecture is described. An example of an apparatus includes of compute front end (CFE) clusters to receive dispatched thread groups, the CFE clusters including at least a first CFE cluster and a second CFE cluster; processing resources coupled with the CFE clusters to execute threads within thread groups; and cache clusters to cache data including thread groups, wherein the apparatus is to receive thread groups for dispatch, and to dispatch the thread groups to the CFE clusters according to a dispatch operation, the dispatch operation including dispatching multiple thread groups to each of multiple CFEs in the first CFE cluster and multiple thread groups to each of multiple CFEs in the second CFE cluster.Type: ApplicationFiled: December 23, 2021Publication date: June 29, 2023Applicant: Intel CorporationInventors: Zamshed Iqbal Chowdhury, Joydeep Ray, Chunhui Mei, Yongsheng Liu, Vasanth Ranganathan, Abhishek R. Appu, Aravindh Anantaraman
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Publication number: 20230206383Abstract: A system includes a compression engine that stores the compression format information embedded in the compressed data. The compression format information can be included in a header that includes compression control surface (CCS) information. The system includes a shared memory to store compressed data for multiple hardware pipelines, where blocks of the compressed data have a common memory footprint and the compression header. The compression engine can compress data to store in the shared memory including generation of the header. The compression engine can decompress data read from the shared memory, including identification of the compression format from the header.Type: ApplicationFiled: December 23, 2021Publication date: June 29, 2023Inventors: Karol A. SZERSZEN, Prasoonkumar SURTI, Vidhya KRISHNAN, Aditya NAVALE, Abhishek R. APPU, Altug KOKER, Ronald W. SILVAS
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Patent number: 11688122Abstract: 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 system may include one or more of a draw call re-orderer communicatively coupled to the application processor and the graphics subsystem to re-order two or more draw calls, a workload re-orderer communicatively coupled to the application processor and the graphics subsystem to re-order two or more work items in an order independent mode, a queue primitive included in at least one of the two or more draw calls to define a producer stage and a consumer stage, and an order-independent executor communicatively coupled to the application processor and the graphics subsystem to provide tile-based order independent execution of a compute stage. Other embodiments are disclosed and claimed.Type: GrantFiled: February 2, 2022Date of Patent: June 27, 2023Assignee: Intel CorporationInventors: Devan Burke, Adam T. Lake, Jeffery S. Boles, John H. Feit, Karthik Vaidyanathan, Abhishek R. Appu, Joydeep Ray, Subramaniam Maiyuran, Altug Koker, Balaji Vembu, Murali Ramadoss, Prasoonkumar Surti, Eric J. Hoekstra, Gabor Liktor, Jonathan Kennedy, Slawomir Grajewski, Elmoustapha Ould-Ahmed-Vall