公开(公告)号：US20180314249A1

公开(公告)日：2018-11-01

申请号：US15581124

申请日：2017-04-28

Applicant: Intel Corporation

Inventor： Abhishek R. Appu ,  John C. Weast ,  Sara S. Baghsorkhi ,  Justin E. Gottschlich ,  Prasoonkumar Surti ,  Chandrasekaran Sakthivel ,  Altug Koker ,  Farshad Akhbari ,  Feng Chen ,  Dukhwan Kim ,  Narayan Srinivasa ,  Nadathur Rajagopalan Satish ,  Kamal Sinha ,  Joydeep Ray ,  Balaji Vembu ,  Mike B. Macpherson ,  Linda L. Hurd ,  Sanjeev Jahagirdar ,  Vasanth Ranganathan

IPC: G05D1/00 ,  G06N3/08 ,  G06N3/04 ,  G06N3/063

CPC classification number: G06F9/5016 ,  G06F9/5061

Abstract: A mechanism is described for facilitating storage management for machine learning at autonomous machines. A method of embodiments, as described herein, includes detecting one or more components associated with machine learning, where the one or more components include memory and a processor coupled to the memory, and where the processor includes a graphics processor. The method may further include allocating a storage portion of the memory and a hardware portion of the processor to a machine learning training set, where the storage and hardware portions are precise for implementation and processing of the training set.

公开(公告)号：US20180308203A1

公开(公告)日：2018-10-25

申请号：US15495081

申请日：2017-04-24

Applicant: Intel Corporation

Inventor： Abhishek R. Appu ,  Altug Koker ,  John C. Weast ,  Mike B. Macpherson ,  Dukhwan Kim ,  Linda L. Hurd ,  Sara S. Baghsorkhi ,  Justin E. Gottschlich ,  Prasoonkumar Surti ,  Chandrasekaran Sakthivel ,  Joydeep Ray

IPC: G06T1/20 ,  G06N3/04 ,  H04L29/08

CPC classification number: G06T1/20 ,  G06F9/5061 ,  G06F9/5072 ,  G06N3/02 ,  G06N3/04 ,  H04L67/10

Abstract: A mechanism is described for facilitating sharing of data and compression expansion of models at autonomous machines. A method of embodiments, as described herein, includes detecting a first processor processing information relating to a neural network at a first computing device, where the first processor comprises a first graphics processor and the first computing device comprises a first autonomous machine. The method further includes facilitating the first processor to store one or more portions of the information in a library at a database, where the one or more portions are accessible to a second processor of a computing device.

公开(公告)号：US20180307983A1

公开(公告)日：2018-10-25

申请号：US15494948

申请日：2017-04-24

Applicant: Intel Corporation

Inventor： Narayan Srinivasa ,  Joydeep Ray ,  Nicolas C. Galoppo Von Borries ,  Ben Ashbaugh ,  Prasoonkumar Surti ,  Feng Chen ,  Barath Lakshmanan ,  Elmoustapha Ould-Ahmed-Vall ,  Liwei Ma ,  Linda L. Hurd ,  Abhishek R. Appu ,  John C. Weast ,  Sara S. Baghsorkhi ,  Justin E. Gottschlich ,  Chandrasekaran Sakthivel ,  Farshad Akhbari ,  Dukhwan Kim ,  Altug Koker ,  Nadathur Rajagopalan Satish

IPC: G06N3/08 ,  G06N3/04

CPC classification number: G06N3/08 ,  G06N3/04 ,  G06N3/0454 ,  G06N3/063 ,  G06N3/082

Abstract: An apparatus to facilitate optimization of a neural network (NN) is disclosed. The apparatus includes optimization logic to define a NN topology having one or more macro layers, adjust the one or more macro layers to adapt to input and output components of the NN and train the NN based on the one or more macro layers.

公开(公告)号：US20180300246A1

公开(公告)日：2018-10-18

申请号：US15489149

申请日：2017-04-17

Applicant: Intel Corporation

Inventor： Chandrasekaran Sakthivel ,  Prasoonkumar Surti ,  John C. Weast ,  Sara S. Baghsorkhi ,  Justin E. Gottschlich ,  Abhishek R. Appu ,  Nicolas C. Galoppo Von Borries ,  Joydeep Ray ,  Narayan Srinivasa ,  Feng Chen ,  Ben J. Ashbaugh ,  Rajkishore Barik ,  Tsung-Han Lin ,  Kamal Sinha ,  Eriko Nurvitadhi ,  Balaji Vembu ,  Altug Koker

IPC: G06F12/0837 ,  G06N3/08 ,  G06N99/00

CPC classification number: G06F12/0837 ,  G06F2212/62 ,  G06N3/08 ,  G06N99/005 ,  G06T1/20

Abstract: In an example, an apparatus comprises a plurality of processing unit cores, a plurality of cache memory modules associated with the plurality of processing unit cores, and a machine learning model communicatively coupled to the plurality of processing unit cores, wherein the plurality of cache memory modules share cache coherency data with the machine learning model. Other embodiments are also disclosed and claimed.

公开(公告)号：US10007549B2

公开(公告)日：2018-06-26

申请号：US14581772

申请日：2014-12-23

Applicant: Intel Corporation

Inventor： Justin E. Gottschlich ,  Gilles A. Pokam ,  Shiliang Hu

IPC: G06F9/44 ,  G06F12/08 ,  G06F9/46 ,  G06F9/445 ,  G06F12/084 ,  G06F9/30 ,  G06F12/0813 ,  G06F12/0811

CPC classification number: G06F9/467 ,  G06F9/3004 ,  G06F9/30087 ,  G06F9/44563 ,  G06F11/3632 ,  G06F12/0811 ,  G06F12/0813 ,  G06F12/084

Abstract: An apparatus and method are described for a hardware transactional memory (HTM) profiler. For example, one embodiment of an apparatus comprises a transactional debugger (TDB) recording module to record data related to the execution of transactional memory program code, including data related to the execution of branches and transactional events in the transactional memory program code; and a profiler to analyze portions of the recorded data using trace-based replay techniques to responsively generate profile data comprising transaction-level events and function-level conflict data usable to optimize the transactional memory program code.

公开(公告)号：US20180173563A1

公开(公告)日：2018-06-21

申请号：US15383738

申请日：2016-12-19

Applicant: Intel Corporation

Inventor： Chunling Hu ,  Tatiana Shpeisman ,  Rajkishore Barik ,  Justin E. Gottschlich

IPC: G06F9/48 ,  G06F9/50

CPC classification number: G06F9/4881 ,  G06F9/5027

Abstract: A dynamic runtime scheduling system includes task manager circuitry capable of detecting a correspondence in at least a portion of the output arguments from one or more first tasks with at least a portion of the input arguments to one or more second tasks. Upon detecting the output arguments from the first task represents a superset of the second task input arguments, the task manager circuitry apportions the first task into a plurality of new subtasks. At least one of the new subtasks includes output arguments having a 1:1 correspondence to the second task input arguments. Upon detecting the output arguments from an first task represents a subset of the second task input arguments, the task manager circuitry may autonomously apportion the second task into a plurality of new subtasks. At least one of the new subtasks may include input arguments having a 1:1 correspondence to first task output arguments.

公开(公告)号：US09128781B2

公开(公告)日：2015-09-08

申请号：US13729718

申请日：2012-12-28

Applicant: Intel Corporation

Inventor： Tim Kranich ,  Gilles A. Pokam ,  Justin E. Gottschlich ,  Klaus Danne ,  Rolf Kassa ,  Shiliang Hu ,  Cristiano L. Pereira

IPC: G06F9/52 ,  G06F11/36

CPC classification number: G06F9/526 ,  G06F11/3404 ,  G06F11/3409 ,  G06F11/3471 ,  G06F11/36 ,  G06F11/3636

Abstract: A processor includes a first core to execute a first software thread, a second core to execute a second software thread, and shared memory access monitoring and recording logic. The logic includes memory access monitor logic to monitor accesses to memory by the first thread, record memory addresses of the monitored accesses, and detect data races involving the recorded memory addresses with other threads. The logic includes chunk generation logic is to generate chunks to represent committed execution of the first thread. Each of the chunks is to include a number of instructions of the first thread executed and committed and a time stamp. The chunk generation logic is to stop generation of a current chunk in response to detection of a data race by the memory access monitor logic. A chunk buffer is to temporarily store chunks until the chunks are transferred out of the processor.

Abstract translation: 处理器包括执行第一软件线程的第一核，执行第二软件线程的第二核和共享存储器存取监视和记录逻辑。 该逻辑包括存储器访问监视器逻辑，以监视第一线程对存储器的访问，记录被监视的访问的存储器地址，以及检测与其他线程相关的记录存储器地址的数据比赛。 逻辑包括块生成逻辑是生成块来表示第一个线程的提交执行。 每个块都包括执行和提交的第一个线程的一些指令和一个时间戳。 块生成逻辑是通过存储器访问监视器逻辑来检测数据竞赛来停止生成当前块。 块缓冲区是临时存储块，直到块被从处理器传出。

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

IPC: G06T1/20 ,  G06F8/41 ,  G06F9/455 ,  G06F9/50 ,  G06N3/044 ,  G06N3/045 ,  G06N3/063 ,  G06N3/084

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.

公开(公告)号：US20240013337A1

公开(公告)日：2024-01-11

申请号：US18351898

申请日：2023-07-13

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

IPC: G06T1/20 ,  G06F9/46 ,  G06N3/063 ,  G06N3/045 ,  G06N3/08

CPC classification number: G06T1/20 ,  G06F9/46 ,  G06N3/063 ,  G06N3/045 ,  G06N3/08 ,  G06N3/084

Abstract: A mechanism is described for detecting, at training time, information related to one or more tasks to be performed by the one or more processors according to a training dataset for a neural network, analyzing the information to determine one or more portions of hardware of a processor of the one or more processors that is configurable to support the one or more tasks, 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, and monitoring utilization of the hardware via a hardware unit of the graphics processor and, via a scheduler of the graphics processor, adjusting allocation of the one or more tasks to the one or more portions of the hardware based on the utilization.

公开(公告)号：US20230012451A1

公开(公告)日：2023-01-12

申请号：US17948222

申请日：2022-09-19

Applicant: Intel Corporation

Inventor： Justin E. Gottschlich ,  Naila Farooqui

IPC: G06N20/00

Abstract: Example methods and apparatus to generate anomaly detection datasets are disclosed. An example method to generate an anomaly detection dataset for training a machine learning model to detect real world anomalies includes receiving a user definition of an anomaly generator function, executing, with a processor, the anomaly generator function to generate user-defined anomaly data, and combining the user-defined anomaly data with nominal data to generate the anomaly detection dataset.