A framework for user-directed profile-driven optimizations

A user and initialization technology, applied in the direction of instrumentation, calculation, electrical digital data processing, etc., can solve the problems of not allowing users to analyze and optimize, labor-intensive, etc.

Active Publication Date: 2016-06-01
GOOGLE LLC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in common runtime libraries these parameters are not tuned, or parameters are tuned for the average application, because customary FDO procedures do not all

Method used

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  • A framework for user-directed profile-driven optimizations
  • A framework for user-directed profile-driven optimizations
  • A framework for user-directed profile-driven optimizations

Examples

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Embodiment Construction

[0021] According to an example embodiment, an architecture may facilitate user-directed profiling-driven optimization by allowing a software developer to profile selected portions of an application and directing the compiler to perform value-profiling transformations based on the profiling results, such as figure 2 shown in . User-defined information can be included in both instrumentation and optimizing compilation of the feedback loop.

[0022] An example method for using profiling to obtain application-specific, preferred parameter values ​​for an application begins by identifying a parameter for which an application-specific value is to be obtained (301), such as image 3 shown in . The enhancement code can then be parsed (302) for application specificity of parameters. In some embodiments, the code to be enhanced may be application code. In other embodiments, the code to be enhanced may be a library used by the application code. This parameter is then parsed specificall

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Abstract

A method for using profiling to obtain application-specific, preferred parameter values for an application is disclosed. First, a parameter for which to obtain an application-specific value is identified (301). Code is then augmented for application-specific profiling of the parameter (302). The parameter is profiled and profile data is collected (303). The profile data is then analyzed to determine the application's preferred parameter value for the profile parameter (304, 305).

Description

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Claims

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Application Information

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Owner GOOGLE LLC
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