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公开(公告)号:US12198221B2
公开(公告)日:2025-01-14
申请号:US18436494
申请日:2024-02-08
Applicant: Intel Corporation
Inventor: 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
Abstract: 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.
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公开(公告)号:US20250005703A1
公开(公告)日:2025-01-02
申请号:US18773094
申请日:2024-07-15
Applicant: Intel Corporation
Inventor: 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
IPC: G06T1/20 , G06F3/14 , G06F9/30 , G06F9/38 , G06N3/044 , G06N3/045 , G06N3/063 , G06N3/084 , G06T15/00 , G06T15/04 , G09G5/36
Abstract: 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.
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公开(公告)号:US20240427679A1
公开(公告)日:2024-12-26
申请号:US18756550
申请日:2024-06-27
Applicant: Intel Corporation
Inventor: Renu Patle , Hanmanthrao Patli , Rakesh Mehta , Hagay Spector , Ivan Herrera Mejia , Fylur Rahman Sathakathulla , Gowtham Raj Karnam , Mohsin Ali , Sahar Sharabi , Abraham Halevi Fraenkel , Eyal Pniel , Ehud Cohn , Raghav Ramesh Lakshmi , Altug Koker
Abstract: Described herein is a generic hardware/software communication (HSC) channel that facilitates the re-use of pre-silicon DPI methods to enable FPGA-based post-silicon validation. The HSC channel translates a DPI interface into a hardware FIFO based mechanism. This translation allows the reuse of the methods without having to re-implement the entire flow in pure hardware. The core logic for the transactor remains the same, while only a small layer of the transactor is converted into the FIFO based mechanism.
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4.
公开(公告)号:US12147302B2
公开(公告)日:2024-11-19
申请号:US17095530
申请日:2020-11-11
Applicant: Intel Corporation
Inventor: Vasanth Ranganathan , Joydeep Ray , Abhishek R. Appu , Nikos Kaburlasos , Lidong Xu , Subramaniam Maiyuran , Altug Koker , Naveen Matam , James Holland , Brent Insko , Sanjeev Jahagirdar , Scott Janus , Durgaprasad Bilagi , Xinmin Tian
IPC: G06F11/10 , G06F12/0802 , G06T1/20 , G06T1/60
Abstract: Apparatuses including a graphics processing unit, graphics multiprocessor, or graphics processor having an error detection correction logic for cache memory or shared memory are disclosed. In one embodiment, a graphics multiprocessor includes cache or local memory for storing data and error detection correction circuitry integrated with or coupled to the cache or local memory. The error detection correction circuitry is configured to perform a tag read for data of the cache or local memory to check error detection correction information.
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公开(公告)号:US12124383B2
公开(公告)日:2024-10-22
申请号:US17862739
申请日:2022-07-12
Applicant: Intel Corporation
Inventor: 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
IPC: G06F12/00 , G06F12/0875 , G06F12/0891 , G06F12/123 , G06T1/60
CPC classification number: G06F12/123 , G06F12/0875 , G06F12/0891 , G06T1/60 , G06F2212/302
Abstract: Systems and methods for improving cache efficiency and 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.
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公开(公告)号:US12093210B2
公开(公告)日:2024-09-17
申请号:US17430574
申请日:2020-03-14
Applicant: Intel Corporation
Inventor: Abhishek R. Appu , Altug Koker , Aravindh Anantaraman , Elmoustapha Ould-Ahmed-Vall , Joydeep Ray , Mike Macpherson , Valentin Andrei , Nicolas Galoppo Von Borries , Varghese George , Subramaniam Maiyuran , Vasanth Ranganathan , Jayakrishna P S , K Pattabhiraman , Sudhakar Kamma
IPC: G06F15/78 , G06F7/544 , G06F7/575 , G06F7/58 , G06F9/30 , G06F9/38 , G06F9/50 , G06F12/02 , G06F12/06 , G06F12/0802 , G06F12/0804 , G06F12/0811 , G06F12/0862 , G06F12/0866 , G06F12/0871 , G06F12/0875 , G06F12/0882 , G06F12/0888 , G06F12/0891 , G06F12/0893 , G06F12/0895 , G06F12/0897 , G06F12/1009 , G06F12/128 , G06F15/80 , G06F17/16 , G06F17/18 , G06T1/20 , G06T1/60 , H03M7/46 , G06N3/08 , G06T15/06
CPC classification number: G06F15/7839 , G06F7/5443 , G06F7/575 , G06F7/588 , G06F9/3001 , G06F9/30014 , G06F9/30036 , G06F9/3004 , G06F9/30043 , G06F9/30047 , G06F9/30065 , G06F9/30079 , G06F9/3887 , G06F9/5011 , G06F9/5077 , G06F12/0215 , G06F12/0238 , G06F12/0246 , G06F12/0607 , G06F12/0802 , G06F12/0804 , G06F12/0811 , G06F12/0862 , G06F12/0866 , G06F12/0871 , G06F12/0875 , G06F12/0882 , G06F12/0888 , G06F12/0891 , G06F12/0893 , G06F12/0895 , G06F12/0897 , G06F12/1009 , G06F12/128 , G06F15/8046 , G06F17/16 , G06F17/18 , G06T1/20 , G06T1/60 , H03M7/46 , G06F9/3802 , G06F9/3818 , G06F9/3867 , G06F2212/1008 , G06F2212/1021 , G06F2212/1044 , G06F2212/302 , G06F2212/401 , G06F2212/455 , G06F2212/60 , G06N3/08 , G06T15/06
Abstract: Methods and apparatus relating to techniques for data compression. In an example, an apparatus comprises a processor receive a data compression instruction for a memory segment; and in response to the data compression instruction, compress a sequence of identical memory values in response to a determination that the sequence of identical memory values has a length which exceeds a threshold. Other embodiments are also disclosed and claimed.
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公开(公告)号:US20240280987A1
公开(公告)日:2024-08-22
申请号:US18595649
申请日:2024-03-05
Applicant: Intel Corporation
Inventor: Abhishek R. Appu , Altug Koker , Joydeep Ray , Balaji Vembu , John C. Weast , Mike B. Macpherson , Dukhwan Kim , Linda L. Hurd , Sanjeev Jahagirdar , Vasanth Ranganathan
IPC: G05D1/00 , G06F9/46 , G06F9/48 , G06F9/52 , G06N3/044 , G06N3/045 , G06N3/063 , G06N3/084 , G06T1/20
CPC classification number: G05D1/0088 , G06F9/4881 , G06F9/522 , G06N3/044 , G06N3/045 , G06N3/063 , G06N3/084 , G06F9/46 , G06T1/20
Abstract: A mechanism is described for facilitating barriers and synchronization for machine learning at autonomous machines. A method of embodiments, as described herein, includes detecting thread groups relating to machine learning associated with one or more processing devices. The method may further include facilitating barrier synchronization of the thread groups across multiple dies such that each thread in a thread group is scheduled across a set of compute elements associated with the multiple dies, where each die represents a processing device of the one or more processing devices, the processing device including a graphics processor.
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公开(公告)号:US20240256456A1
公开(公告)日:2024-08-01
申请号:US18391346
申请日:2023-12-20
Applicant: Intel Corporation
Inventor: 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
IPC: G06F12/0862 , G06T1/20 , G06T1/60
CPC classification number: G06F12/0862 , G06T1/20 , G06T1/60 , G06F2212/602 , G06F2212/608
Abstract: 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.
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9.
公开(公告)号:US20240184572A1
公开(公告)日:2024-06-06
申请号:US18528340
申请日:2023-12-04
Applicant: Intel Corporation
Inventor: 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
IPC: G06F9/30 , G06F7/483 , G06F7/544 , G06F9/38 , G06F17/16 , G06N3/044 , G06N3/045 , G06N3/063 , G06N3/08 , G06N20/00 , G06T15/00 , G09G5/393
CPC classification number: G06F9/3001 , G06F7/483 , G06F7/5443 , G06F9/30014 , G06F9/30036 , G06F9/3851 , G06N3/044 , G06N3/045 , G06N3/063 , G06N3/08 , G09G5/393 , G06F9/30025 , G06F9/3013 , G06F17/16 , G06F2207/3824 , G06N20/00 , G06T15/005
Abstract: 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.
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10.
公开(公告)号:US20240152457A1
公开(公告)日:2024-05-09
申请号:US18531432
申请日:2023-12-06
Applicant: Intel Corporation
Inventor: Altug Koker
IPC: G06F12/0815 , G06F12/0804 , G06F12/0811 , G06F12/1009 , G06F12/1045
CPC classification number: G06F12/0815 , G06F12/0804 , G06F12/0811 , G06F12/1009 , G06F12/1045 , G06F12/1063 , G06F2212/1021 , G06F2212/1024 , G06F2212/281 , G06F2212/302 , G06F2212/608 , G06F2212/656 , G06F2212/657 , G06F2212/68 , G06F2212/682 , G06F2212/684
Abstract: Embodiments described herein provide a scalable coherency tracking implementation that utilizes shared virtual memory to manage data coherency. In one embodiment, coherency tracking granularity is reduced relative to existing coherency tracking solutions, with coherency tracking storage memory moved to memory as a page table metadata. For example and in one embodiment, storage for coherency state is moved from dedicated hardware blocks to system memory, effectively providing a directory structure that is limitless in size.
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