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Progress Report

Progress Report. 2012/12/20. Computation Offloading. Mobile devices have limited energy and computing resources. Offloading some workloads to remote servers leads to: Power-saving. Performance improving. Shorter execution time. Better results. Our Idea.

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Progress Report

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  1. Progress Report 2012/12/20

  2. Computation Offloading • Mobile devices have limited energy and computing resources. • Offloading some workloads to remote servers leads to: • Power-saving. • Performance improving. • Shorter execution time. • Better results.

  3. Our Idea • Instead of studying offloading policies, we aim at the effects caused by offloading. • After offloading, a computation-intensive process becomes I/O-intensive. • Does this phenomenon affects scheduler? • Does this phenomenon affects DVFS? • Does this phenomenon affects cache/memory? • …etc.

  4. Problem • Service thread • Computation-intensive => I/O-intensive • Task in waiting state will not be scheduled.

  5. Current Flow Offloading Framework Scheduler DVFS DPM Load change

  6. New strategy • The original idea of virtual core is: Computation Offloading C-task Remote cores N cores N+1 cores

  7. New strategy(Cont.) • 反其道而行 • Close a core after offloading Computation Offloading C-task Remote cores N cores N-1 cores

  8. Reason • After offloading, the rest of the tasks will be scheduled to N cores. • Should have better performance. • Does not guarantee energy saving. • All the cores are still working! • If we close a core after offloading • Imagine that the computation-intensive task is non-preemptive, but consume zero power. • Energy saving with little effect to (other tasks) performance.

  9. New Flow Offloading Framework Scheduler DVFS DPM

  10. Comparison

  11. However • This is a theoretically strategy. • Need to design some experiments to verify the strategy.

  12. Possible Topics • Close more cores • -1?-2?-n/2?-(n-1)? • Close which core(s) • The one executing the offloaded task? • Cache related • Theoretical problem • Math model

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