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(2007)Conference PaperMinimising energy use is an important factor in the operation of many classes of embedded systems - in particular, battery-powered devices. Dynamic voltage and frequency scaling (DVFS) provides some control over a processor's performance and energy consumption. In order to employ DVFS for managing a system's energy use, it is necessary to predict the effect this scaling has on the system's total energy consumption. Simple (yet widely-used) energy models lead to dramatically incorrect results for important classes of application programs. Predicting the energy used under scaling requires (i) a prediction of the dependency of program performance (and hence duration of execution) on the frequencies and (ii) a prediction of the power drawn by the execution as a function of the frequencies and voltages. As both of these characteristics are workload-specific our approach builds a model that, given a workload execution at one frequency setpoint, will predict the run-time and power at any other frequency setpoint. We assume temporal locality (which is valid for the vast majority of applications) so predicting the characteristics of one time slice, frame, or other instance of a task, will imply the characteristics of subsequent time slices, frames or instances (e.g. MPEG video decoding). We present a systematic approach to building these models for a hardware platform, determining the best performance counters and weights. This characterisation, done once for a particular platform, produces platform-specific but workload-independent performance and power models. We implemented the model on a real system and evaluated it under a comprehensive benchmark suite against measurements of the actual energy consumption. The results show that the model can accurately predict the energy use of a wide class of applications and is highly responsive to changes in the application behaviour.
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(2007)Conference PaperIn 1992 Wang & Larsen extended the may- and must preorders of De Nicola and Hennessy to processes featuring probabilistic as well as nondeterministic choice. They concluded with two problems that have remained open throughout the years, namely to find complete axiomatisations and alternative characterisations for these preorders. This paper solves both problems for finite processes with silent moves. It characterises the may preorder in terms of simulation, and the must preorder in terms of failure simulation. It also gives a characterisation of both preorders using a modal logic. Finally it axiomatises both preorders over a probabilistic version of CSP.
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