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公开(公告)号:US11217040B2
公开(公告)日:2022-01-04
申请号:US16383849
申请日:2019-04-15
Applicant: Intel Corporation
Inventor: 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
IPC: G05D1/00 , G07C5/00 , G08G1/01 , H04W28/08 , H04L29/08 , G06N20/00 , G06F9/50 , G01C21/34 , B60W30/00 , G06N3/04 , G06N3/063 , G06N3/08 , G06N20/10 , G08G1/052 , G01S19/13 , H04L12/26 , G05D1/02
Abstract: One embodiment provides for a computing device within an autonomous vehicle, the compute device comprising a wireless network device to enable a wireless data connection with an autonomous vehicle network, a set of multiple processors including a general-purpose processor and a general-purpose graphics processor, the set of multiple processors to execute a compute manager to manage execution of compute workloads associated with the autonomous vehicle, the compute workload associated with autonomous operations of the autonomous vehicle, and offload logic configured to execute on the set of multiple processors, the offload logic to determine to offload one or more of the compute workloads to one or more autonomous vehicles within range of the wireless network device.
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公开(公告)号:US20210201438A1
公开(公告)日:2021-07-01
申请号:US17143805
申请日:2021-01-07
Applicant: Intel Corporation
Inventor: 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
Abstract: A mechanism is described for facilitating inference coordination and processing utilization for machine learning at autonomous machines. A method of embodiments, as described herein, includes detecting, at training time, information relating to one or more tasks to be performed according to a training dataset relating to a processor including a graphics processor. The method may further include analyzing the information to determine one or more portions of hardware relating to the processor capable of supporting the one or more tasks, and 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.
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公开(公告)号:US10332320B2
公开(公告)日:2019-06-25
申请号:US15488914
申请日:2017-04-17
Applicant: Intel Corporation
Inventor: 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
IPC: G01C22/00 , G07C5/00 , G05D1/00 , G01C21/34 , G08G1/01 , H04W28/08 , G06N20/00 , G06F9/50 , G08G1/052 , G01S19/13 , G05D1/02 , H04L29/08 , H04L12/26
Abstract: One embodiment provides for a computing device within an autonomous vehicle, the compute device comprising a wireless network device to enable a wireless data connection with an autonomous vehicle network, a set of multiple processors including a general-purpose processor and a general-purpose graphics processor, the set of multiple processors to execute a compute manager to manage execution of compute workloads associated with the autonomous vehicle, the compute workload associated with autonomous operations of the autonomous vehicle, and offload logic configured to execute on the set of multiple processors, the offload logic to determine to offload one or more of the compute workloads to one or more autonomous vehicles within range of the wireless network device.
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公开(公告)号:US20190146800A1
公开(公告)日:2019-05-16
申请号:US16227645
申请日:2018-12-20
Applicant: Intel Corporation
Inventor: ELMOUSTAPHA OULD-AHMED-VALL , BARATH LAKSHMANAN , TATIANA SHPEISMAN , Joydeep Ray , Ping T. Tang , Michael Strickland , Xiaoming Chen , Anbang Yao , Ben J. Ashbaugh , Linda L. Hurd , Liwei Ma
IPC: G06F9/38 , G06N20/00 , G06F15/80 , G06F13/42 , G06F9/30 , G06F13/40 , G06T1/20 , G06N3/00 , G06F9/50
Abstract: One embodiment provides for a general-purpose graphics processing unit comprising a streaming multiprocessor having a single instruction, multiple thread (SIMT) architecture including hardware multithreading. The streaming multiprocessor comprises multiple processing blocks including multiple processing cores. The processing cores include independent integer and floating-point data paths that are configurable to concurrently execute multiple independent instructions. A memory is coupled with the multiple processing blocks.
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公开(公告)号:US20180315157A1
公开(公告)日:2018-11-01
申请号:US15581167
申请日:2017-04-28
Applicant: Intel Corporation
Inventor: Elmoustapha Ould-Ahmed-Vall , Sara S. Baghsorkhi , Anbang Yao , Kevin Nealis , Xiaoming Chen , Altug Koker , Abhishek R. Appu , John C. Weast , Mike B. Macpherson , Dukhwan Kim , Linda L. Hurd , Ben . Ashbaugh , Barath Lakshmanan , Liwei Ma , Joydeep Ray , Ping T. Tang , Michael S. Strickland
Abstract: One embodiment provides a general-purpose graphics processing unit comprising a dynamic precision floating-point unit including a control unit having precision tracking hardware logic to track an available number of bits of precision for computed data relative to a target precision, wherein the dynamic precision floating-point unit includes computational logic to output data at multiple precisions.
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公开(公告)号:US20180307495A1
公开(公告)日:2018-10-25
申请号:US15819167
申请日:2017-11-21
Applicant: Intel Corporation
Inventor: ELMOUSTAPHA OULD-AHMED-VALL , BARATH LAKSHMANAN , TATIANA SHPEISMAN , Joydeep Ray , Ping T. Tang , Michael Strickland , Xiaoming Chen , Anbang Yao , Ben J. Ashbaugh , Linda L. Hurd , Liwei Ma
CPC classification number: G06F9/3887 , G06F9/3001 , G06F9/30014 , G06F9/30036 , G06F9/30094 , G06F9/30109 , G06F9/30112 , G06F9/3016 , G06F9/3802 , G06F9/3836 , G06F9/3851 , G06F9/50 , G06F13/4068 , G06F13/4282 , G06F15/80 , G06F2213/0026 , G06N3/00 , G06N99/005 , G06T1/20
Abstract: One embodiment provides for a graphics processing unit (GPU) to accelerate machine learning operations, the GPU comprising an instruction cache to store a first instruction and a second instruction, the first instruction to cause the GPU to perform a floating-point operation, including a multi-dimensional floating-point operation, and the second instruction to cause the GPU to perform an integer operation; and a general-purpose graphics compute unit having a single instruction, multiple thread (SIMT) architecture, the general-purpose graphics compute unit to simultaneously execute the first instruction and the second instruction, wherein the integer operation corresponds to a memory address calculation.
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公开(公告)号:US20180293205A1
公开(公告)日:2018-10-11
申请号:US15482796
申请日:2017-04-09
Applicant: Intel Corporation
Inventor: Altug Koker , Farshad Akhbari , Feng Chen , Dukhwan Kim , Narayan Srinivasa , Nadathur Rajagopalan Satish , Liwei Ma , Jeremy Bottleson , Eriko Nurvitadhi , Joydeep Ray , Ping T. Tang , Michael Strickland , Xiaoming Chen , Tatiana Shpeisman , Abhishek R. Appu
CPC classification number: G06F15/8007 , G06F9/3004 , G06F13/00 , G06F13/4027 , G06N3/0445 , G06N3/0454 , G06N3/0481 , G06N3/063 , G06N3/084 , G06T1/20
Abstract: An integrated circuit (IC) package apparatus is disclosed. The IC package includes one or more processing units and a bridge, mounted below the one or more processing unit, including one or more arithmetic logic units (ALUs) to perform atomic operations.
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公开(公告)号:US20250117874A1
公开(公告)日:2025-04-10
申请号:US18908445
申请日:2024-10-07
Applicant: Intel Corporation
Inventor: Elmoustapha Ould-Ahmed-Vall , Sara S. Baghsorkhi , Anbang Yao , Kevin Nealis , Xiaoming Chen , Altug Koker , Abhishek R. Appu , John C. Weast , Mike B. Macpherson , Dukhwan Kim , Linda L. Hurd , Ben J. Ashbaugh , Barath Lakshmanan , Liwei Ma , Joydeep Ray , Ping T. Tang , Michael S. Strickland
Abstract: One embodiment provides an apparatus comprising a memory stack including multiple memory dies and a parallel processor including a plurality of multiprocessors. Each multiprocessor has a single instruction, multiple thread (SIMT) architecture, the parallel processor coupled to the memory stack via one or more memory interfaces. At least one multiprocessor comprises a multiply-accumulate circuit to perform multiply-accumulate operations on matrix data in a stage of a neural network implementation to produce a result matrix comprising a plurality of matrix data elements at a first precision, precision tracking logic to evaluate metrics associated with the matrix data elements and indicate if an optimization is to be performed for representing data at a second stage of the neural network implementation, and a numerical transform unit to dynamically perform a numerical transform operation on the matrix data elements based on the indication to produce transformed matrix data elements at a second precision.
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公开(公告)号:US20240086683A1
公开(公告)日:2024-03-14
申请号:US18471843
申请日:2023-09-21
Applicant: Intel Corporation
Inventor: Liwei Ma , Nadathur Rajagopalan Satish , Jeremy Bottleson , Farshad Akhbari , Eriko Nurvitadhi , Chandrasekaran Sakthivel , Barath Lakshmanan , Jingyi Jin , Justin E. Gottschlich , Michael Strickland
CPC classification number: G06N3/044 , G06F9/5038 , G06N3/045 , G06N3/063 , G06N3/084 , G06F2209/5021
Abstract: 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.
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公开(公告)号:US11810318B2
公开(公告)日:2023-11-07
申请号:US16326005
申请日:2016-09-09
Applicant: Intel Corporation
Inventor: Liwei Ma
CPC classification number: G06T7/73 , G06N3/08 , G06T2207/20081 , G06T2207/20084 , G06T2207/30244
Abstract: A mechanism is described for facilitating training and deploying of pose regression in neural networks in autonomous machines. A method, as described herein, includes facilitating capturing, by an image capturing device of a computing device, one or more images of one or more objects, where the one or more images include one or more training images associated with a neural network. The method may further include continuously estimating, in real-time, a present orientation of the computing device, where estimating includes continuously detecting a real-time view field as viewed by the image capturing device and based on the one or more images. The method may further include applying pose regression relating to the image capturing device using the real-time view field.
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