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The Anole framework involves three modules: energy profiler is a module used for estimating application energy consumption, energy-aware APIs that state applications by using the energy information and energy-aware policy which applies the energy adaptation of operating system by including service and hardware adaptations.
As power-driven adaptation of shared resources affects multiple threads at once, the efficiency in a tile-organized many-core processor architecture hinges on the ability to co-schedule compatible threads to tiles in tandem with hardware adaptations per tile and per core.
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Results are presented in terms of performance (frames per second), resource utilization, and run-time hardware adaptation for a variety of hardware design parameters, video resolutions, and self-reconfigurability scenarios.
Unfortunately, as core count grows, the complexity of both the adaptation hardware and the power management algorithms increases exponentially.
On the other hand, the linearly interpolated adaptation requires two memory reads and writes per data sample, placing more stringent timing requirements on the adaptation hardware.
This technique assumes adaptation of hardware architecture to fit its structure to the currently performed algorithm.
Approaches for reducing the power consumption in DSL can be classified into three categories[19]: the optimization of hardware components; dynamic rate adaptation (e.g., by spectral optimization); and low-power modes.
Loudness was further transformed in both hardware and software for adaptation to the hearing range.
The advantage of the upper-layer adaptation is that it can be widely used on different PHY/MAC hardware and protocols since the adaptation is independent of the PHY/MAC layer protocols.
SDRCS requires no extra hardware for localization, transmission power adaptation or multi-channel transmission.
To support late-bound, runtime adaptation to various hardware platforms, the SCORE runtime employs a paged reconfiguration discipline.
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