1 / 19

Frequency Setting for Energy Minimization in Multimedia Applications

This study presents an energy minimization technique through processor frequency setting in streaming multimedia applications. The research covers power optimization models, algorithms, and experimental results to show significant power consumption reduction. By adjusting the CPU clock frequency based on real-time frames and synchronization constraints, the proposed approach effectively lowers power consumption without compromising performance. The experimental findings demonstrate substantial energy savings, highlighting the efficiency of the frequency-energy relationship in multimedia processing.

zorion
Télécharger la présentation

Frequency Setting for Energy Minimization in Multimedia Applications

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Processor Frequency Setting for Energy Minimization of Streaming Multimedia Application by A. Acquaviva, L. Benini, and B. Riccò, in Proc. 9th Internation Symposium on Hardware/Software Codesign, Apr. 2001.

  2. Agenda • Introduction • Power optimization model derivation • Power optimization algorithm • Experimental results • Conclusion

  3. Introduction • With technology enhancement, multimedia capabilities are being added to handheld devices. Examples: • Picture taking • MP3 audio playback • Video playback • Audio recording • A new problem arises  power management

  4. Introduction • Power management options • Shut down devices when in idle mode • Problem: Background tasks have to be stopped as well • Better approaches: clock frequency and voltageregulation • Lowers system speed in idle states • Reduces LCD display brightness

  5. Introduction • Real-time media streaming applications • Retrieve stream data from off-CPU interface (e.g. discs, memory cards) • Process data (e.g. decoding, decompression) • Deliver processed data to output interface (e.g. display, speakers)

  6. Power Optimization Model Derivation • System settings: • The CPU must communicate with relatively slower I/O interfaces • Clock frequency can be adjusted by software • Frame-based media (e.g. MP3 audio, MPEG video)

  7. Power Optimization Model Derivation • Power consumption: • Energy per frame: V – supply voltage, C – switched capacitance, f – CPU clock frequency, Tf– frame processing time, Nf – number of cycles to process frame, t – cycle time

  8. Power Optimization Model Derivation • Due to speed difference between the CPU and external hardware: where Nidle is a non-decreasing function of f • We now have

  9. Power Optimization Model Derivation • To satisfy real-time synchronization constraint: Tmax – maximum allowed time for a frame (e.g. 1/30s in 30fps movie)

  10. Power Optimization Model Derivation • In words, target of power optimization is to reduce the term Nidle in under the constraint

  11. Power Optimization Model Derivation • This technique is more effective if application requires much memory access • However, delay and energy spent for frequency adjustment must also be considered

  12. Proposed Algorithm • Define three curves FRB(f), FRA(f), FRW(f), the best-case, average-case and worst-case frame rate at f. • Compute curves for all bit rate and sampling rate values and obtain FRoB(f), FRoA(f), FRoW(f) • Compute FRreq by • Nsample : samples per frame, fixed at 576 for MP1 and MP1 phase 2

  13. Proposed Algorithm • Normalize the curves FRoB(f), FRoA(f), FRoW(f) by FRoA(fmax) from a pre-calculated look-up table • Intersect FRreq with three curves to obtain fmin, fav and fmax.

  14. Proposed Algorithm • CPU frequency can be set to: • fmin if we find constantly frames processed faster than the average rate • favif we want continuous playback, with some buffering storage for decoding rate jitter • fmax to guarantee real-time performance on a frame-by-frame basis • Greater than fmax if the processor is not dedicated to the application only

  15. Experimental Results • Energy consumption per frame

  16. Experimental Results • Energy consumption for 16KHz, 16KBit/s audio

  17. Experimental Results • Frequency setting

  18. Example Calculation • An audio stream of 16KHz, 16KBit/s • Without any optimization, Ef = 10.989mJ • FRreq = 16000 / 576 = 27.78 fps • FRA(fmax) = 65.36 fps • Normalized FR = 27.8 / 65.36 = 0.425 fps • fmin = 85.7MHz, fmax = 106.7MHz • Choosing fmax, Ef = 8.9mJ  19% energy reduction

  19. Conclusion • Frequency-energy relationship is derived • An energy optimization algorithm is proposed • Experiment shows dramatic save in power consumption

More Related