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In this study, we explore a novel method to model GPU power consumption of applications in computing process.
This traditional approach limits the mapping, partitioning and the generation of optimized parallel code, and consequently the achievable performance and power consumption of applications from different domains.
Accounting for the CPU consumption of applications is crucial for software development to detect and remove performance bottlenecks (profiling) and to evaluate the performance of algorithms (benchmarking).
The dependency of these devices on battery as the main power source imposed strict constraints on the energy consumption of applications that run on these mobile devices.
These approaches are unable to estimate power consumption of applications for software designers owing to the lack of information about detailed GPUs architecture or the supporting of emulators.
In the approach presented here, program transformations enable resource management in Java-based environments, even though the underlying runtime system may not expose information concerning the resource consumption of applications.
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In addition, by generalizing the analysis of the two applications, a conceptual framework is created with which to analyse the consumption pattern of applications in their early development phases.
It is a framework that aims to tell application designers the changing time of the energy consumption states of applications.
To determine the overall power consumption of an application a, all application profiles must be considered.
Only recently have end users been afforded the ability to access the power consumption of their applications.
This conceptual framework will allow mobile developers to estimate the resource consumption of their applications under different conditions of software architecture and usage scenarios, providing them with information relevant for decision making.
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