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• W2061781141 abstract "We investigate deadline scheduling of independent tasks on parallel processors with discrete frequency levels, when the latency for frequency scaling cannot be neglected. This situation frequently occurs in applications, e.g. streaming applications with soft real-time requirements. We demonstrate that previous algorithms for energy-optimal static scheduling of independent tasks are non-optimal in this setting. We present a scheduling heuristic based on bin packing with a cost function that takes latency for frequency scaling into account. We evaluate our heuristic against previous approaches with benchmark task sets and achieve energy reductions between 3% and 13%. We further demonstrate that for a concrete embedded multicore processor, the power curves vary over the identical cores, so that the processor looks heterogeneous from a power perspective. We adapt our bin packing heuristic and demonstrate that for the benchmark task sets, further energy reductions up to 4% can be achieved." @default.
• W2061781141 created "2016-06-24" @default.
• W2061781141 creator A5018765427 @default.
• W2061781141 creator A5072565571 @default.
• W2061781141 date "2015-03-01" @default.
• W2061781141 modified "2023-09-27" @default.
• W2061781141 title "Energy-Efficient Task Scheduling in Manycore Processors with Frequency Scaling Overhead" @default.
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• W2061781141 doi "https://doi.org/10.1109/pdp.2015.64" @default.
• W2061781141 hasPublicationYear "2015" @default.
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