公开(公告)号：US20200167193A1

公开(公告)日：2020-05-28

申请号：US16776338

申请日：2020-01-29

Applicant: Apple Inc.

Inventor： Francesco ROSSI ,  Gaurav KAPOOR ,  Michael R. SIRACUSA ,  William B. MARCH

IPC: G06F9/50 ,  G06F8/41 ,  G06N3/02 ,  G06N3/063

Abstract: The subject technology provides for dynamic task allocation for neural network models. The subject technology determines an operation performed at a node of a neural network model. The subject technology assigns an annotation to indicate whether the operation is better performed on a CPU or a GPU based at least in part on hardware capabilities of a target platform. The subject technology determines whether the neural network model includes a second layer. The subject technology, in response to determining that the neural network model includes a second layer, for each node of the second layer of the neural network model, determines a second operation performed at the node. Further the subject technology assigns a second annotation to indicate whether the second operation is better performed on the CPU or the GPU based at least in part on the hardware capabilities of the target platform.

公开(公告)号：US20170249344A1

公开(公告)日：2017-08-31

申请号：US15374946

申请日：2016-12-09

Applicant: Apple Inc.

Inventor： Stephen C. PETERS ,  Kit-Man WAN ,  Gaurav KAPOOR

IPC: G06F17/30 ,  G06F3/0484 ,  G06F3/0488 ,  G06F3/0481 ,  G06F3/0482

CPC classification number: G06F16/23 ,  G06F3/04817 ,  G06F3/0482 ,  G06F3/04842 ,  G06F3/04847 ,  G06F3/04883

Abstract: This application relates to features for a mobile device that allow the mobile device to assign utility values to applications and thereafter suggest applications for a user to execute. The suggested application can be derived from a list of applications that have been assigned a utility by software in the mobile device. The utility assignment of the individual applications from the list of applications can be performed based on the occurrence of an event, an environmental change, or a period of frequent application usage. A feedback mechanism is provided in some embodiments for more accurately assigning a utility to particular applications. The feedback mechanism can track what a user does during a period of suggestion for certain applications and thereafter modify the utility of applications based on what applications a user selects during the period of suggestion.

公开(公告)号：US20140164757A1

公开(公告)日：2014-06-12

申请号：US13913307

申请日：2013-06-07

Applicant: Apple Inc.

Inventor： John G. DORSEY ,  James S. ISMAIL ,  Keith COX ,  Gaurav KAPOOR

IPC: G06F1/32

CPC classification number: G09G5/003 ,  G06F1/20 ,  G06F1/26 ,  G06F1/324 ,  G06F1/3296 ,  G06T1/20 ,  G06T1/60 ,  G06T13/80 ,  G06T2200/28 ,  G09G5/18 ,  G09G2354/00 ,  G09G2360/08 ,  G09G2360/127 ,  Y02D10/126 ,  Y02D10/172

Abstract: The invention provides a technique for targeted scaling of the voltage and/or frequency of a processor included in a computing device. One embodiment involves scaling the voltage/frequency of the processor based on the number of frames per second being input to a frame buffer in order to reduce or eliminate choppiness in animations shown on a display of the computing device. Another embodiment of the invention involves scaling the voltage/frequency of the processor based on a utilization rate of the GPU in order to reduce or eliminate any bottleneck caused by slow issuance of instructions from the CPU to the GPU. Yet another embodiment of the invention involves scaling the voltage/frequency of the CPU based on specific types of instructions being executed by the CPU. Further embodiments include scaling the voltage and/or frequency of a CPU when the CPU executes workloads that have characteristics of traditional desktop/laptop computer applications.

Abstract translation: 本发明提供了一种用于针对包括在计算设备中的处理器的电压和/或频率进行目标缩放的技术。 一个实施例涉及基于每秒输入帧缓冲器的帧数来缩放处理器的电压/频率，以便减少或消除在计算设备的显示器上显示的动画中的笨拙。 本发明的另一实施例涉及基于GPU的利用率来缩放处理器的电压/频率，以便减少或消除由CPU向GPU缓慢发出指令所引起的任何瓶颈。 本发明的另一个实施例涉及根据由CPU执行的特定类型的指令来调整CPU的电压/频率。 另外的实施例包括在CPU执行具有传统台式/膝上型计算机应用的特征的工作负载时缩放CPU的电压和/或频率。

公开(公告)号：US20240362199A1

公开(公告)日：2024-10-31

申请号：US18766360

申请日：2024-07-08

Applicant: Apple Inc.

Inventor： Stephen C. PETERS ,  Kit-Man WAN ,  Gaurav KAPOOR

IPC: G06F16/23 ,  G06F3/04817 ,  G06F3/0482 ,  G06F3/04842 ,  G06F3/04847 ,  G06F3/04883

CPC classification number: G06F16/23 ,  G06F3/04817 ,  G06F3/0482 ,  G06F3/04842 ,  G06F3/04847 ,  G06F3/04883

Abstract: This application relates to features for a mobile device that allow the mobile device to assign utility values to applications and thereafter suggest applications for a user to execute. The suggested application can be derived from a list of applications that have been assigned a utility by software in the mobile device. The utility assignment of the individual applications from the list of applications can be performed based on the occurrence of an event, an environmental change, or a period of frequent application usage. A feedback mechanism is provided in some embodiments for more accurately assigning a utility to particular applications. The feedback mechanism can track what a user does during a period of suggestion for certain applications and thereafter modify the utility of applications based on what applications a user selects during the period of suggestion.

公开(公告)号：US20210326230A1

公开(公告)日：2021-10-21

申请号：US17221256

申请日：2021-04-02

Applicant: Apple Inc.

Inventor： Cyril DE LA CROPTE DE CHANTERAC ,  Phillip STANLEY-MARBELL ,  Kartik VENKATRAMAN ,  Gaurav KAPOOR

IPC: G06F11/32 ,  G06F1/3203 ,  G06F1/3212

Abstract: Systems and methods are disclosed for advising a user when an energy storage device in a computing system needs charging. State of charge data of the energy storage device can be measured and stored at regular intervals. The historic state of charge data can be queried over a plurality of intervals and a state of charge curve generated that is representative of a user's charging habits over time. The state of charge curve can be used to generate a rate of charge histogram and an acceleration of charge histogram. These can be used to predict when a user will charge next, and whether the energy storage device will have an amount of energy below a predetermined threshold amount before the next predicted charging time. A first device can determine when a second device typically charges and whether the energy storage device in the second device will have an amount of energy below the predetermined threshold amount before the next predicted charge time for the second device. The first device can generate an advice to charge notification to the user on either, or both, devices.

公开(公告)号：US20200382616A1

公开(公告)日：2020-12-03

申请号：US16554518

申请日：2019-08-28

Applicant: Apple Inc.

Inventor： Umesh S. VAISHAMPAYAN ,  Gaurav KAPOOR ,  Kit-man WAN

IPC: H04L29/08 ,  G06N20/00 ,  H04W4/021 ,  G06F3/0488

Abstract: In an exemplary process for remote execution of machine-learned models, one or more signals from a second electronic device is detected by a first electronic device. The second electronic device includes a machine-learned model associated with an application implemented on the first electronic device. Based on the one or more signals, a communication connection is established with the second electronic device and a proxy to the machine-learned model is generated. Input data is obtained via a sensor of the first electronic device. A representation of the input data is sent to the second electronic device via the proxy and the established communication connection. The representation of the input data is processed through the machine-learned model to generate an output. A result derived from the output is received via the communication connection and a representation of the result is outputted.

公开(公告)号：US20200082274A1

公开(公告)日：2020-03-12

申请号：US16262809

申请日：2019-01-30

Applicant: Apple Inc.

Inventor： Francesco ROSSI ,  Cecile M. FORET ,  Gaurav KAPOOR ,  Kit-Man WAN ,  Umesh S. VAISHAMPAYAN ,  Etienne BELANGER ,  Albert ANTONY ,  Alexey MARINICHEV ,  Marco ZULIANI ,  Xiaojin SHI

IPC: G06N3/10 ,  G06N3/04 ,  G06N3/08

Abstract: The subject technology provides receiving a neural network (NN) model to be executed on a target platform, the NN model including multiple layers that include operations and some of the operations being executable on multiple processors of the target platform. The subject technology further sorts the operations from the multiple layers in a particular order based at least in part on grouping the operations that are executable by a particular processor of the multiple processors. The subject technology determines, based at least in part on a cost of transferring the operations between the multiple processors, an assignment of one of the multiple processors for each of the sorted operations of each of the layers in a manner that minimizes a total cost of executing the operations. Further, for each layer of the NN model, the subject technology includes an annotation to indicate the processor assigned for each of the operations.

公开(公告)号：US20200082273A1

公开(公告)日：2020-03-12

申请号：US16262807

申请日：2019-01-30

Applicant: Apple Inc.

Inventor： Francesco ROSSI ,  Cecile M. FORET ,  Gaurav KAPOOR ,  Kit-Man WAN ,  Umesh S. VAISHAMPAYAN ,  Etienne BELANGER

IPC: G06N3/10 ,  G06F9/48

Abstract: The subject technology runs a compiled neural network (NN) model on a particular processor with multiple priority queues for executing different processes, the compiled NN model being assigned to a particular priority queue, and the compiled NN model includes context switch instructions that were previously inserted into a neural network (NN) model from which the compiled NN model was compiled. The subject technology determines that a particular context switch instruction has been executed by the particular processor. The subject technology determines that a different process is waiting to be executed, the different process being assigned to a different priority queue and the different process being a higher priority process than the running compiled NN model. In response to executing the particular context switch instruction, the subject technology performs a context switch to the different process assigned to the different priority queue when the different process is waiting to be executed.

公开(公告)号：US20180349103A1

公开(公告)日：2018-12-06

申请号：US15721712

申请日：2017-09-29

Applicant: Apple Inc.

Inventor： Alexander B. BROWN ,  Michael R. SIRACUSA ,  Gaurav KAPOOR ,  Elizabeth OTTENS ,  Christopher M. HANSON ,  Zachary A. NATION ,  Vrushali MUNDHE ,  Srikrishna SRIDHAR

IPC: G06F9/44 ,  G06N99/00

CPC classification number: G06F8/315 ,  G06F8/10 ,  G06F8/30 ,  G06F8/35 ,  G06F8/36 ,  G06F8/60 ,  G06F8/71 ,  G06N99/005

Abstract: The subject technology provides for determining that a machine learning model in a first format includes sufficient data to conform to a particular model specification in a second format, the second format corresponding to an object oriented programming language. The subject technology transforms the machine learning model into a transformed machine learning model that is compatible with the particular model specification. The subject technology generates a code interface and code for the transformed machine learning model, the code interface including code statements in the object oriented programming language, the code statements corresponding to an object representing the transformed machine learning model. Further, the subject technology provides the generated code interface and the code for display in an integrated development environment (IDE), the IDE enabling modifying of the generated code interface and the code.

公开(公告)号：US20150348228A1

公开(公告)日：2015-12-03

申请号：US14821665

申请日：2015-08-07

Applicant: Apple Inc.

Inventor： John G. DORSEY ,  James S. ISMAIL ,  Keith COX ,  Gaurav KAPOOR

IPC: G06T1/20 ,  G09G5/18 ,  G09G5/00

CPC classification number: G09G5/003 ,  G06F1/20 ,  G06F1/26 ,  G06F1/324 ,  G06F1/3296 ,  G06T1/20 ,  G06T1/60 ,  G06T13/80 ,  G06T2200/28 ,  G09G5/18 ,  G09G2354/00 ,  G09G2360/08 ,  G09G2360/127 ,  Y02D10/126 ,  Y02D10/172

Abstract: The invention provides a technique for targeted scaling of the voltage and/or frequency of a processor included in a computing device. One embodiment involves scaling the voltage/frequency of the processor based on the number of frames per second being input to a frame buffer in order to reduce or eliminate choppiness in animations shown on a display of the computing device. Another embodiment of the invention involves scaling the voltage/frequency of the processor based on a utilization rate of the GPU in order to reduce or eliminate any bottleneck caused by slow issuance of instructions from the CPU to the GPU. Yet another embodiment of the invention involves scaling the voltage/frequency of the CPU based on specific types of instructions being executed by the CPU. Further embodiments include scaling the voltage and/or frequency of a CPU when the CPU executes workloads that have characteristics of traditional desktop/laptop computer applications.

Abstract translation: 本发明提供了一种用于针对包括在计算设备中的处理器的电压和/或频率进行目标缩放的技术。 一个实施例涉及基于每秒输入帧缓冲器的帧数来缩放处理器的电压/频率，以便减少或消除在计算设备的显示器上显示的动画中的笨拙。 本发明的另一实施例涉及基于GPU的利用率来缩放处理器的电压/频率，以便减少或消除由CPU向GPU缓慢发出指令所引起的任何瓶颈。 本发明的另一个实施例涉及根据由CPU执行的特定类型的指令来调整CPU的电压/频率。 另外的实施例包括在CPU执行具有传统台式/膝上型计算机应用的特征的工作负载时缩放CPU的电压和/或频率。