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Frame-based dynamic voltage and frequency scaling for a MPEG decoder
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FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
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Compiler-directed dynamic voltage and frequency scaling for cpu power and energy reduction
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Extended MPEG Video Format for Efficient Dynamic Voltage Scaling
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Run-time adaptive workload estimation for dynamic voltage scaling
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Compiler-directed dynamic voltage scaling using program phases
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ACM Transactions on Embedded Computing Systems (TECS)
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This paper describes a dynamic voltage and frequency scaling (DVFS) technique for MPEG decoding to reduce the energy consumption using the computational workload decomposition. This technique decomposes the workload for decoding a frame into on-chip and off-chip workloads. The execution time required for the on-chip workload is CPU frequency-dependent, whereas the off-chip workload execution time does not change, regardless of the CPU frequency, resulting in the maximum energy savings by setting the minimum frequency during off-chip workload execution time, without causing any delay penalty. This workload decomposition is performed using a performance-monitoring unit (PMU) in the XScale-processor, which provides various statistics such as cache hit/miss and CPU stall, due to data dependency at run time. The on-chip workload for an incoming frame is predicted using a frame-based history so that the processor voltage and frequency can be scaled to provide the exact amount of computing power needed to decode the frame. To guarantee a quality of service (QoS) constraint, a prediction error compensation method, called inter-frame compensation, is proposed in which the on-chip workload prediction error is diffused into subsequent frames such that run time frame rates change smoothly. The proposed DVFS algorithm has been implemented on an XScale-based Testbed. Detailed current measurements on this platform demonstrate significant CPU energy savings ranging from 50% to 80% depending on the video clip.