Patents by Inventor Subramaniam Maiyuran

Subramaniam Maiyuran 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: 20210374897
    Abstract: Embodiments described herein include, software, firmware, and hardware logic that provides techniques to perform arithmetic on sparse data via a systolic processing unit. Embodiment described herein provided techniques to skip computational operations for zero filled matrices and sub-matrices. Embodiments additionally provide techniques to maintain data compression through to a processing unit. Embodiments additionally provide an architecture for a sparse aware logic unit.
    Type: Application
    Filed: June 3, 2021
    Publication date: December 2, 2021
    Applicant: Intel Corporation
    Inventors: Joydeep Ray, Scott Janus, Varghese George, Subramaniam Maiyuran, Altug Koker, Abhishek Appu, Prasoonkumar Surti, Vasanth Ranganathan, Andrei Valentin, Ashutosh Garg, Yoav Harel, Arthur Hunter, JR., SungYe Kim, Mike Macpherson, Elmoustapha Ould-Ahmed-Vall, William Sadler, Lakshminarayanan Striramassarma, Vikranth Vemulapalli
  • Patent number: 11188618
    Abstract: An apparatus to facilitate acceleration of matrix multiplication operations. The apparatus comprises a systolic array including matrix multiplication hardware to perform multiply-add operations on received matrix data comprising data from a plurality of input matrices and sparse matrix acceleration hardware to detect zero values in the matrix data and perform one or more optimizations on the matrix data to reduce multiply-add operations to be performed by the matrix multiplication hardware.
    Type: Grant
    Filed: September 5, 2019
    Date of Patent: November 30, 2021
    Assignee: Intel Corporation
    Inventors: Subramaniam Maiyuran, Mathew Nevin, Jorge Parra, Ashutosh Garg, Shubra Marwaha, Shubh Shah
  • Publication number: 20210365402
    Abstract: An apparatus to facilitate computing efficient cross channel operations in parallel computing machines using systolic arrays is disclosed. The apparatus includes a plurality of registers and one or more processing elements communicably coupled to the plurality of registers. The one or more processing elements include a systolic array circuit to perform cross-channel operations on source data received from a single source register of the plurality of registers, the systolic array circuit modified to receive inputs from the single source register and route elements of the single source register to multiple channels in the systolic array circuit.
    Type: Application
    Filed: June 12, 2020
    Publication date: November 25, 2021
    Applicant: Intel Corporation
    Inventors: Subramaniam Maiyuran, Jorge Parra, Supratim Pal, Chandra Gurram
  • Patent number: 11182337
    Abstract: An apparatus to facilitate computing efficient cross channel operations in parallel computing machines using systolic arrays is disclosed. The apparatus includes a plurality of registers and one or more processing elements communicably coupled to the plurality of registers. The one or more processing elements include a systolic array circuit to perform cross-channel operations on source data received from a single source register of the plurality of registers, the systolic array circuit modified to receive inputs from the single source register and route elements of the single source register to multiple channels in the systolic array circuit.
    Type: Grant
    Filed: June 12, 2020
    Date of Patent: November 23, 2021
    Assignee: INTEL CORPORATION
    Inventors: Subramaniam Maiyuran, Jorge Parra, Supratim Pal, Chandra Gurram
  • Publication number: 20210357618
    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: April 2, 2021
    Publication date: November 18, 2021
    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: 11176736
    Abstract: Methods, systems and apparatuses may provide for technology that determines the size of a graphics primitive, renders pixels associated with the graphics primitive on a per tile basis if the size exceeds a threshold, and renders the pixels associated with the graphics primitive in a mesh order if the size does not exceed the threshold. In one example, the technology discards state data associated with the graphics primitive in response to a completion of rendering the pixels associated with the graphics primitive in the mesh order.
    Type: Grant
    Filed: January 21, 2021
    Date of Patent: November 16, 2021
    Assignee: Intel Corporation
    Inventors: Justin DeCell, Saurabh Sharma, Subramaniam Maiyuran, Raghavendra Miyar, Jorge Garcia Pabon
  • Publication number: 20210350499
    Abstract: An apparatus to facilitate compute optimization is disclosed. The apparatus includes a plurality of processing units each comprising a plurality of processing cores of a first type and a second type. A first set of processing cores of a first type perform multi-dimensional matrix operations and a second set of processing cores of a second type perform general purpose graphics processing unit (GPGPU) operations.
    Type: Application
    Filed: July 26, 2021
    Publication date: November 11, 2021
    Applicant: Intel Corporation
    Inventors: 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
  • Publication number: 20210349966
    Abstract: Described herein is an accelerator device including a host interface, a fabric interconnect coupled with the host interface, and one or more hardware tiles coupled with the fabric interconnect, the one or more hardware tiles including sparse matrix multiply acceleration hardware including a systolic array with feedback inputs.
    Type: Application
    Filed: June 26, 2020
    Publication date: November 11, 2021
    Applicant: Intel Corporation
    Inventors: SUBRAMANIAM MAIYURAN, JORGE PARRA, SUPRATIM PAL, ASHUTOSH GARG, SHUBRA MARWAHA, CHANDRA GURRAM, DARIN STARKEY, DURGESH BORKAR, VARGHESE GEORGE
  • Publication number: 20210349717
    Abstract: Described herein is an accelerator device in which compaction of diverged lanes of a parallel processor is enabled to increase the efficiency of ALU utilization. One embodiment provides an accelerator device comprising a host interface, a fabric interconnect coupled with the host interface, and one or more hardware tiles coupled with the fabric interconnect, the one or more hardware tiles including a parallel processing architecture configured to enable compaction of diverged lanes.
    Type: Application
    Filed: June 26, 2020
    Publication date: November 11, 2021
    Applicant: Intel Corporation
    Inventors: Chandra Gurram, Subramaniam Maiyuran, Supratim Pal, Saurabh Sharma, Aditya Navale
  • Publication number: 20210349715
    Abstract: In an example, an apparatus comprises a plurality of execution units, and a first general register file (GRF) communicatively couple to the plurality of execution units, wherein the first GRF is shared by the plurality of execution units. Other embodiments are also disclosed and claimed.
    Type: Application
    Filed: May 12, 2021
    Publication date: November 11, 2021
    Applicant: Intel Corporation
    Inventors: Abhishek R. Appu, Altug Koker, Joydeep Ray, Kamal Sinha, Kiran C. Veernapu, Subramaniam Maiyuran, Prasoonkumar Surti, Guei-Yuan Lueh, David Puffer, Supratim Pal, Eric J. Hoekstra, Travis T. Schluessler, Linda L. Hurd
  • Publication number: 20210349848
    Abstract: Methods and apparatus relating to scalar core integration in a graphics processor. In an example, an apparatus comprises a processor to receive a set of workload instructions for a graphics workload from a host complex, determine a first subset of operations in the set of operations that is suitable for execution by a scalar processor complex of the graphics processing device and a second subset of operations in the set of operations that is suitable for execution by a vector processor complex of the graphics processing device, assign the first subset of operations to the scalar processor complex for execution to generate a first set of outputs, assign the second subset of operations to the vector processor complex for execution to generate a second set of outputs. Other embodiments are also disclosed and claimed.
    Type: Application
    Filed: May 17, 2021
    Publication date: November 11, 2021
    Applicant: Intel Corporation
    Inventors: JOYDEEP RAY, ARAVINDH ANANTARAMAN, ABHISHEK R. APPU, ALTUG KOKER, ELMOUSTAPHA OULD-AHMED-VALL, VALENTIN ANDREI, SUBRAMANIAM MAIYURAN, NICOLAS GALOPPO VON BORRIES, VARGHESE GEORGE, MIKE MACPHERSON, BEN ASHBAUGH, MURALI RAMADOSS, VIKRANTH VEMULAPALLI, WILLIAM SADLER, JONATHAN PEARCE, SUNGYE KIM
  • Patent number: 11169850
    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: Grant
    Filed: December 24, 2019
    Date of Patent: November 9, 2021
    Assignee: INTEL CORPORATION
    Inventors: Abhishek R Appu, Altug Koker, Balaji Vembu, Joydeep Ray, Kamal Sinha, Prasoonkumar Surti, Kiran C. Veernapu, Subramaniam Maiyuran, Sanjeev S. Jahagirdar, Eric J. Asperheim, Guei-Yuan Lueh, David Puffer, Wenyin Fu, Nikos Kaburlasos, Bhushan M. Borole, Josh B. Mastronarde, Linda L. Hurd, Travis T. Schluessler, Tomasz Janczak, Abhishek Venkatesh, Kai Xiao, Slawomir Grajewski
  • Patent number: 11163578
    Abstract: Mechanisms for reducing register bank conflicts based on software hint and hardware thread switch are disclosed. In some embodiments, an apparatus for thread switching includes a graphics processing unit (GPU) that includes a plurality of register banks to store operands that are assigned at least partially to avoid register bank conflicts. Decoding circuitry checks a thread switching field of a first instruction to be executed by a first thread. The GPU performs a thread switch mechanism to cause a second instruction to be executed by a second thread when the thread switching field of the first instruction is set.
    Type: Grant
    Filed: February 23, 2018
    Date of Patent: November 2, 2021
    Assignee: Intel Corporation
    Inventors: Buqi Cheng, Wei-Yu Chen, Guei-Yuan Lueh, Chandra Gurram, Subramaniam Maiyuran
  • Patent number: 11157238
    Abstract: Embodiments described herein are generally directed to an improved vector normalization instruction. An embodiment of a method includes responsive to receipt by a GPU of a single instruction specifying a vector normalization operation to be performed on V vectors: (i) generating V squared length values, N at a time, by a first processing unit, by, for each N sets of inputs, each representing multiple component vectors for N of the vectors, performing N parallel dot product operations on the N sets of inputs. Generating V sets of outputs representing multiple normalized component vectors of the V vectors, N at a time, by a second processing unit, by, for each N squared length values of the V squared length values, performing N parallel operations on the N squared length values, wherein each of the N parallel operations implement a combination of a reciprocal square root function and a vector scaling function.
    Type: Grant
    Filed: November 15, 2019
    Date of Patent: October 26, 2021
    Assignee: Intel Corporation
    Inventors: Abhishek Rhisheekesan, Supratim Pal, Shashank Lakshminarayana, Subramaniam Maiyuran
  • Publication number: 20210326176
    Abstract: Accelerated synchronization operations using fine grain dependency check are disclosed. A graphics multiprocessor includes a plurality of execution units and synchronization circuitry that is configured to determine availability of at least one execution unit. The synchronization circuitry to perform a fine grain dependency check of availability of dependent data or operands in shared local memory or cache when at least one execution unit is available.
    Type: Application
    Filed: May 11, 2021
    Publication date: October 21, 2021
    Applicant: Intel Corporation
    Inventors: Subramaniam Maiyuran, Varghese George, Altug Koker, Aravindh Anantaraman, SungYe Kim, Valentin Andrei, Joydeep Ray
  • Publication number: 20210312697
    Abstract: Described herein is a graphics processing unit (GPU) comprising a single instruction, multiple thread (SIMT) multiprocessor comprising an instruction cache, a shared memory coupled with the instruction cache, and circuitry coupled with the shared memory and the instruction cache, the circuitry including multiple texture units, a first core including hardware to accelerate matrix operations, and a second core configured to receive an instruction having multiple operands in a bfloat16 (BF16) number format, wherein the multiple operands include a first source operand, a second source operand, and a third source operand, and the BF16 number format is a sixteen-bit floating point format having an eight-bit exponent and process the instruction, wherein to process the instruction includes to multiply the second source operand by the third source operand and add a first source operand to a result of the multiply.
    Type: Application
    Filed: June 14, 2021
    Publication date: October 7, 2021
    Applicant: Intel Corporation
    Inventors: Subramaniam Maiyuran, Shubra Marwaha, Ashutosh Garg, Supratim Pal, Jorge Parra, Chandra Gurram, Varghese George, Darin Starkey, Guei-Yuan Lueh
  • Publication number: 20210303299
    Abstract: Embodiments described herein provided for an instruction and associated logic to enable GPGPU program code to access special purpose hardware logic to accelerate dot product operations. One embodiment provides for a graphics processing unit comprising a fetch unit to fetch an instruction for execution and a decode unit to decode the instruction into a decoded instruction. The decoded instruction is a matrix instruction to cause the graphics processing unit to perform a parallel dot product operation. The GPGPU also includes systolic dot product circuitry to execute the decoded instruction across one or more SIMD lanes using multiple systolic layers, wherein to execute the decoded instruction, a dot product computed at a first systolic layer is to be output to a second systolic layer, wherein each systolic layer includes one or more sets of interconnected multipliers and adders, each set of multipliers and adders to generate a dot product.
    Type: Application
    Filed: June 15, 2021
    Publication date: September 30, 2021
    Applicant: Intel Corporation
    Inventors: SUBRAMANIAM MAIYURAN, GUEI-YUAN LUEH, SUPRATIM PAL, ASHUTOSH GARG, CHANDRA S. GURRAM, JORGE E. PARRA, JUNJIE GU, KONRAD TRIFUNOVIC, HONG BIN LIAO, MIKE B. MACPHERSON, SHUBH B. SHAH, SHUBRA MARWAHA, STEPHEN JUNKINS, TIMOTHY R. BAUER, VARGHESE GEORGE, WEIYU CHEN
  • Patent number: 11119820
    Abstract: One embodiment provides for a general-purpose graphics processing unit comprising a set of processing elements to execute one or more thread groups of a second kernel to be executed by the general-purpose graphics processor, an on-chip memory coupled to the set of processing elements, and a scheduler coupled with the set of processing elements, the scheduler to schedule the thread groups of the kernel to the set of processing elements, wherein the scheduler is to schedule a thread group of the second kernel to execute subsequent to a thread group of a first kernel, the thread group of the second kernel configured to access a region of the on-chip memory that contains data written by the thread group of the first kernel in response to a determination that the second kernel is dependent upon the first kernel.
    Type: Grant
    Filed: March 15, 2019
    Date of Patent: September 14, 2021
    Assignee: Intel Corporation
    Inventors: Valentin Andrei, Aravindh Anantaraman, Abhishek R. Appu, Nicolas C. Galoppo von Borries, Altug Koker, SungYe Kim, Elmoustapha Ould-Ahmed-Vall, Mike Macpherson, Subramaniam Maiyuran, Vasanth Ranganathan, Joydeep Ray, Varghese George
  • Publication number: 20210279177
    Abstract: An apparatus to facilitate data prefetching is disclosed. The apparatus includes a cache, one or more execution units (EUs) to execute program code, prefetch logic to maintain tracking information of memory instructions in the program code that trigger a cache miss and compiler logic to receive the tracking information, insert one or more pre-fetch instructions in updated program code to prefetch data from a memory for execution of one or more of the memory instructions that triggered a cache miss and download the updated program code for execution by the one or more EUs.
    Type: Application
    Filed: March 24, 2021
    Publication date: September 9, 2021
    Applicant: Intel Corporation
    Inventors: Vasileios Porpodas, Guei-Yuan Lueh, Subramaniam Maiyuran, Wei-Yu Chen
  • Patent number: 11113784
    Abstract: Embodiments described herein include, software, firmware, and hardware logic that provides techniques to perform arithmetic on sparse data via a systolic processing unit. Embodiment described herein provided techniques to skip computational operations for zero filled matrices and sub-matrices. Embodiments additionally provide techniques to maintain data compression through to a processing unit. Embodiments additionally provide an architecture for a sparse aware logic unit.
    Type: Grant
    Filed: October 6, 2020
    Date of Patent: September 7, 2021
    Assignee: Intel Corporation
    Inventors: Joydeep Ray, Scott Janus, Varghese George, Subramaniam Maiyuran, Altug Koker, Abhishek Appu, Prasoonkumar Surti, Vasanth Ranganathan, Andrei Valentin, Ashutosh Garg, Yoav Harel, Arthur Hunter, Jr., SungYe Kim, Mike Macpherson, Elmoustapha Ould-Ahmed-Vall, William Sadler, Lakshminarayanan Striramassarma, Vikranth Vemulapalli