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Application characterization for machine learning on heterogeneous core devices

A technology for computing equipment and users, applied in machine learning, instrumentation, program control design, etc., can solve the problem of not caring about the delay of complex algorithms for face detection

Inactive Publication Date: 2017-08-01
QUALCOMM INC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

As another example, when a photo is taken to be uploaded to a social media site, the user may write a status that accompanies the photo and, therefore, may not be concerned with the delay of complex algorithms for face detection

Method used

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  • Application characterization for machine learning on heterogeneous core devices
  • Application characterization for machine learning on heterogeneous core devices
  • Application characterization for machine learning on heterogeneous core devices

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Experimental program
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Embodiment Construction

[0023] Various aspects will be described in detail with reference to the accompanying drawings. Wherever possible, the same reference numbers will be used throughout the drawings to refer to the same or like parts. References made to specific examples and implementations are for illustrative purposes, and are not intended to limit the scope of the invention or the claims.

[0024] The word "exemplary" is used herein to mean "serving as an example, instance, or illustration." Any implementation described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other implementations.

[0025] The term "computing device" is used herein to refer to any or all of the following: cellular phones, smartphones, web-pads, tablet computers, Internet-enabled cellular phones, functional electronic devices, personal data assistants (PDAs), laptop computers, personal computers, and similar electronic devices equipped with at least one processor. For examp...

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PUM

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Abstract

The present invention relates to methods, devices, systems, and non-transitory process-readable storage media for a computing device to use machine learning to dynamically configure an application and / or complex algorithms associated with the application. An aspect method performed by a processor of the computing device may include operations for performing an application that calls a library function associated with a complex algorithm, obtaining signals indicating user responses to performance of the application, determining whether a user tolerates the performance of the application based on the obtained signals indicating the user responses, adjusting a configuration of the application to improve a subsequent performance of the application in response to determining the user does not tolerate the performance of the application, and storing data indicating the user responses to the performance of the application and other external variables for use in subsequent evaluations of user inputs.

Description

[0001] related application [0002] This application claims the benefit of priority to U.S. Provisional Application No. 62 / 091,290, filed December 12, 2014, entitled "Application Characterization for Machine Learning on Heterogeneous Core Devices," and filed December 12, 2014 U.S. Provisional Application No. 62 / 091,132, filed on the 12th, entitled "Architecture for Improving Dynamic Execution of Complex Algorithms", the entire contents of these two applications are hereby incorporated by reference. Background technique [0003] Many user equipment applications may use some complex algorithms (also known as computing kernels). For example, a social media application could be configured to call a library that solves linear systems, provides matrix multiplication, performs eigenvalue decomposition, and more. Such complex algorithms typically require significant computing resources, and thus, when executed at the highest execution speed and / or precision settings, can greatly impa...

Claims

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Application Information

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IPC IPC(8): G06F11/34G06N99/00G06N20/00
CPCG06N20/00G06F11/3438G06F9/542Y02D10/00
Inventor F·穆罕默德米尔扎伊V·斯里哈拉N·伊斯兰
Owner QUALCOMM INC
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