Patents by Inventor Joydeep Ray
Joydeep Ray 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: 12066975Abstract: Embodiments are generally directed to cache structure and utilization. An embodiment of an apparatus includes one or more processors including a graphics processor; a memory for storage of data for processing by the one or more processors; and a cache to cache data from the memory; wherein the apparatus is to provide for dynamic overfetching of cache lines for the cache, including receiving a read request and accessing the cache for the requested data, and upon a miss in the cache, overfetching data from memory or a higher level cache in addition to fetching the requested data, wherein the overfetching of data is based at least in part on a current overfetch boundary, and provides for data is to be prefetched extending to the current overfetch boundary.Type: GrantFiled: March 14, 2020Date of Patent: August 20, 2024Assignee: INTEL CORPORATIONInventors: Altug Koker, Lakshminarayanan Striramassarma, Aravindh Anantaraman, Valentin Andrei, Abhishek R. Appu, Sean Coleman, Varghese George, K Pattabhiraman, Mike MacPherson, Subramaniam Maiyuran, ElMoustapha Ould-Ahmed-Vall, Vasanth Ranganathan, Joydeep Ray, S Jayakrishna P, Prasoonkumar Surti
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Patent number: 12061831Abstract: In accordance with some embodiments, the render rate is varied across and/or up and down the display screen. This may be done based on where the user is looking in order to reduce power consumption and/or increase performance. Specifically the screen display is separated into regions, such as quadrants. Each of these regions is rendered at a rate determined by at least one of what the user is currently looking at, what the user has looked at in the past and/or what it is predicted that the user will look at next. Areas of less focus may be rendered at a lower rate, reducing power consumption in some embodiments.Type: GrantFiled: September 26, 2023Date of Patent: August 13, 2024Assignee: Intel CorporationInventors: Eric J. Asperheim, Subramaniam Maiyuran, Kiran C. Veernapu, Sanjeev S. Jahagirdar, Balaji Vembu, Devan Burke, Philip R. Laws, Kamal Sinha, Abhishek R. Appu, Elmoustapha Ould-Ahmed-Vall, Peter L. Doyle, Joydeep Ray, Travis T. Schluessler, John H. Feit, Nikos Kaburlasos, Jacek Kwiatkowski, Altug Koker
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Publication number: 20240264657Abstract: In one embodiment, a processor includes: a graphics processor to execute a workload; and a power controller coupled to the graphics processor. The power controller may include a voltage ramp circuit to receive a request for the graphics processor to operate at a first performance state having a first operating voltage and a first operating frequency and cause an output voltage of a voltage regulator to increase to the first operating voltage. The voltage ramp circuit may be configured to enable the graphics processor to execute the workload at an interim performance state having an interim operating voltage and an interim operating frequency when the output voltage reaches a minimum operating voltage. Other embodiments are described and claimed.Type: ApplicationFiled: March 11, 2024Publication date: August 8, 2024Inventors: Altug Koker, Abhishek R. Appu, Bhushan M. Borole, Wenyin Fu, Kamal Sinha, Joydeep Ray
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Patent number: 12056906Abstract: 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: September 13, 2023Date of Patent: August 6, 2024Assignee: 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: 12056788Abstract: An apparatus to facilitate compute optimization is disclosed. The apparatus includes a mixed precision core including mixed-precision execution circuitry to execute one or more of the mixed-precision instructions to perform a mixed-precision dot-product operation comprising to perform a set of multiply and accumulate operations.Type: GrantFiled: March 1, 2022Date of Patent: August 6, 2024Assignee: Intel CorporationInventors: 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
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Patent number: 12056059Abstract: Systems and methods for cache utilization are disclosed. In one embodiment, a graphics processor includes processing resources to perform graphics operations and a cache controller of a cache memory that is coupled to the processing resources. The cache controller is configured to set an initial aging policy using an aging field based on age of cache lines within the cache memory and to determine whether a hint or an instruction to indicate a level of aging has been received. In one embodiment, the cache memory configured to be partitioned into multiple cache regions, wherein the multiple cache regions include a first cache region having a cache eviction policy with a configurable level of data persistence.Type: GrantFiled: February 1, 2022Date of Patent: August 6, 2024Assignee: Intel CorporationInventors: Altug Koker, Joydeep Ray, Elmoustapha Ould-Ahmed-Vall, Abhishek Appu, Aravindh Anantaraman, Valentin Andrei, Durgaprasad Bilagi, Varghese George, Brent Insko, Sanjeev Jahagirdar, Scott Janus, Pattabhiraman K, SungYe Kim, Subramaniam Maiyuran, Vasanth Ranganathan, Lakshminarayanan Striramassarma, Xinmin Tian
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Publication number: 20240256825Abstract: A library of machine learning primitives is provided to optimize a machine learning model to improve the efficiency of inference operations. In one embodiment a trained convolutional neural network (CNN) model is processed into a trained CNN model via pruning, convolution window optimization, and quantization.Type: ApplicationFiled: February 7, 2024Publication date: August 1, 2024Applicant: 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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Publication number: 20240257294Abstract: 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 8, 2024Publication date: August 1, 2024Applicant: 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: 20240256483Abstract: Embodiments are generally directed to graphics processor data access and sharing. An embodiment of an apparatus includes a circuit element to produce a result in processing of an application; a load-store unit to receive the result and generate pre-fetch information for a cache utilizing the result; and a prefetch generator to produce prefetch addresses based at least in part on the pre-fetch information; wherein the load-store unit is to receive software assistance for prefetching, and wherein generation of the pre-fetch information is based at least in part on the software assistance.Type: ApplicationFiled: January 17, 2024Publication date: August 1, 2024Applicant: Intel CorporationInventors: Altug Koker, Varghese George, Aravindh Anantaraman, Valentin Andrei, Abhishek R. Appu, Niranjan Cooray, Nicolas Galoppo Von Borries, Mike MacPherson, Subramaniam Maiyuran, ElMoustapha Ould-Ahmed-Vall, David Puffer, Vasanth Ranganathan, Joydeep Ray, Ankur N. Shah, Lakshminarayanan Striramassarma, Prasoonkumar Surti, Saurabh Tangri
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Publication number: 20240256456Abstract: Embodiments are generally directed to data prefetching for graphics data processing. An embodiment of an apparatus includes one or more processors including one or more graphics processing units (GPUs); and a plurality of caches to provide storage for the one or more GPUs, the plurality of caches including at least an L1 cache and an L3 cache, wherein the apparatus to provide intelligent prefetching of data by a prefetcher of a first GPU of the one or more GPUs including measuring a hit rate for the Li cache; upon determining that the hit rate for the L1 cache is equal to or greater than a threshold value, limiting a prefetch of data to storage in the L3 cache, and upon determining that the hit rate for the L1 cache is less than a threshold value, allowing the prefetch of data to the L1 cache.Type: ApplicationFiled: December 20, 2023Publication date: August 1, 2024Applicant: Intel CorporationInventors: Vikranth Vemulapalli, Lakshminarayanan Striramassarma, Mike MacPherson, Aravindh Anantaraman, Ben Ashbaugh, Murali Ramadoss, William B. Sadler, Jonathan Pearce, Scott Janus, Brent Insko, Vasanth Ranganathan, Kamal Sinha, Arthur Hunter, Jr., Prasoonkumar Surti, Nicolas Galoppo von Borries, Joydeep Ray, Abhishek R. Appu, ElMoustapha Ould-Ahmed-Vall, Altug Koker, Sungye Kim, Subramaniam Maiyuran, Valentin Andrei
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Patent number: 12050502Abstract: Described herein are various embodiments of reducing dynamic power consumption within a processor device. One embodiment provides a technique for dynamic link width adjustment based on throughput demand for client of an interconnect fabric. One embodiment provides for a parallel processor comprising an interconnect fabric including a dynamically configurable bus widths and frequencies.Type: GrantFiled: June 1, 2023Date of Patent: July 30, 2024Inventors: Mohammed Tameem, Altug Koker, Kiran C. Veernapu, Abhishek R. Appu, Ankur N. Shah, Joydeep Ray, Travis T. Schluessler, Jonathan Kennedy
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Patent number: 12039000Abstract: An apparatus to facilitate machine learning matrix processing is disclosed. The apparatus comprises a memory to store matrix data one or more processors to execute an instruction to examine a message descriptor included in the instruction to determine a type of matrix layout manipulation operation that is to be executed, examine a message header included in the instruction having a plurality of parameters that define a two-dimensional (2D) memory surface that is to be retrieved, retrieve one or more blocks of the matrix data from the memory based on the plurality of parameters and a register file including a plurality of registers, wherein the one or more blocks of the matrix data is stored within a first set of the plurality of registers.Type: GrantFiled: February 2, 2023Date of Patent: July 16, 2024Assignee: Intel CorporationInventors: Joydeep Ray, Fangwen Fu, Dhiraj D. Kalamkar, Sasikanth Avancha
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Patent number: 12039331Abstract: One embodiment provides for a graphics processing unit to accelerate machine-learning operations, the graphics processing unit comprising a multiprocessor having a single instruction, multiple thread (SIMT) architecture, the multiprocessor to execute at least one single instruction; and a first compute unit included within the multiprocessor, the at least one single instruction to cause the first compute unit to perform a two-dimensional matrix multiply and accumulate operation, wherein to perform the two-dimensional matrix multiply and accumulate operation includes to compute an intermediate product of 16-bit operands and to compute a 32-bit sum based on the intermediate product.Type: GrantFiled: October 17, 2022Date of Patent: July 16, 2024Assignee: 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: 20240231621Abstract: Embodiments described herein provide a technique to enable access to entries in a surface state or sampler state using 64-bit virtual addresses. One embodiment provides a graphics core that includes memory access circuitry configured to facilitate access to the memory by functional units of the graphics core. The memory access circuitry is configured to receive a message to access an entry in a surface state or a sampler state associated with a parallel processing operation. The message specifies a base address for a surface state entry or sampler state entry. The circuitry can add the base address and the offset to determine a 64-bit virtual address for the entry in the surface state entry or the sampler state and submit a memory access request to the memory to access the entry of the surface state or sampler state.Type: ApplicationFiled: October 21, 2022Publication date: July 11, 2024Applicant: Intel CorporationInventors: Joydeep Ray, Michael Apodaca, Yoav Harel, Guei-Yuan Lueh, John A. Wiegert
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Publication number: 20240232088Abstract: Embodiments described herein provide a technique to facilitate the broadcast or multicast of asynchronous loads to shared local memory of a plurality of graphics cores within a graphics core cluster. One embodiment provides a graphics processor including a cache memory a graphics core cluster coupled with the cache memory. The graphics core cluster includes a plurality of graphics cores. The plurality of graphics cores includes a graphics core configured to receive a designation as a producer graphics core for a multicast load, read data from the cache memory; and transmit the data read from the cache memory to a consumer graphics core of the plurality of graphics cores.Type: ApplicationFiled: October 25, 2022Publication date: July 11, 2024Applicant: Intel CorporationInventors: John A. Wiegert, Joydeep Ray, Vasanth Ranganathan, Biju George, Fangwen Fu, Abhishek R. Appu, Chunhui Mei, Changwon Rhee
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Publication number: 20240232094Abstract: 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: January 5, 2024Publication date: July 11, 2024Applicant: 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: 12032496Abstract: An apparatus to facilitate efficient data sharing for graphics data processing operations is disclosed. The apparatus includes a processing resource to generate a stream of instructions, an L1 cache communicably coupled to the processing resource and comprising an on-page detector circuit to determine that a set of memory requests in the stream of instructions access a same memory page; and set a marker in a first request of the set of memory requests; and arbitration circuitry communicably coupled to the L1 cache, the arbitration circuitry to route the set of memory requests to memory comprising the memory page and to, in response to receiving the first request with the marker set, remain with the processing resource to process the set of memory requests.Type: GrantFiled: July 25, 2023Date of Patent: July 9, 2024Assignee: INTEL CORPORATIONInventors: Joydeep Ray, Altug Koker, Elmoustapha Ould-Ahmed-Vall, Michael Macpherson, Aravindh V. Anantaraman, Vasanth Ranganathan, Lakshminarayanan Striramassarma, Varghese George, Abhishek Appu, Prasoonkumar Surti
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Publication number: 20240221295Abstract: One embodiment provides for a graphics processing unit comprising a processing cluster to perform multi-rate shading via coarse pixel shading and output shaded coarse pixels for processing by a post-shader pixel processing pipeline.Type: ApplicationFiled: February 8, 2024Publication date: July 4, 2024Applicant: Intel CorporationInventors: Prasoonkumar Surti, Abhishek R. Appu, Subhajit Dasgupta, Srivallaba Mysore, Michael J. Norris, Vasanth Ranganathan, Joydeep Ray
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Publication number: 20240211403Abstract: One embodiment provides a graphics processor comprising memory access circuitry configured to generate a virtual address for pixel data at a pixel coordinate on a surface in memory to facilitate the caching of the pixel data in a cache memory before the actual memory address of the pixel coordinate is able to be determined.Type: ApplicationFiled: December 21, 2022Publication date: June 27, 2024Applicant: Intel CorporationInventors: Abhishek R. Appu, Joydeep Ray, Karthik Vaidyanathan, Sreedhar Chalasani, Eric Liskay, Prathamesh Raghunath Shinde, Vasanth Ranganathan, Michael J. Norris, Rajasekhar Pantangi, Altug Koker
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Patent number: 12020135Abstract: A library of machine learning primitives is provided to optimize a machine learning model to improve the efficiency of inference operations. In one embodiment a trained convolutional neural network (CNN) model is processed into a trained CNN model via pruning, convolution window optimization, and quantization.Type: GrantFiled: August 26, 2021Date of Patent: June 25, 2024Assignee: 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
