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Published byAriel Leonard Modified over 9 years ago
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Evaluating Impact of Storage on Smartphone Energy Efficiency David T. Nguyen
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LIFE IN MOBILE ERA.. 1,038,000,000 SMARTPHONE USERS WORLDWIDE [IBTIMES] 27% INCREASED # SMARTPHONES SOLD ANNUALLY [IDC] Figure Courtesy: http://www.ideas4ios.comhttp://www.ideas4ios.com David T. Nguyen2
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SMARTPHONE APPS DO EVERYTHING! 850,000 APPS IN APPLE STORE 05/13 [APPLE] 800,000 APPS IN GOOGLE PLAY 05/13 [CANALYS] 145,000 APPS IN WINDOWS STORE 05/13 [CANALYS] 120,000 APPS IN BLACKBERRY WORLD 05/13 [CANALYS] Figure Courtesy: http://aptito.com http://aptito.com David T. Nguyen3
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Still BIG Problem David T. Nguyen4 Figure Courtesy: http://cdn.cultofmac.comhttp://cdn.cultofmac.com
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Smartphone Dislikes David T. Nguyen5 Source: ChangeWave
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Outline Introduction Background Experimental Study Pilot Solution Evaluation David T. Nguyen6
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Introduction Researching energy consumption essential What has been done ◦ Performance bottleneck in storage [Kim et al., FAST ‘12] ◦ No direct study of storage – energy consumption correlation David T. Nguyen7
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Introduction Thesis Statement ◦ Investigate impact of storage on smartphone energy efficiency ◦ Explain root reasons of such impact ◦ Develop storage-aware energy saving solutions Expected Contributions ◦ Better understanding of storage subsystem and its impact on energy efficiency ◦ Storage-aware energy saving solutions David T. Nguyen8
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Outline Introduction Background Experimental Study Pilot Solution Evaluation David T. Nguyen9
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I/O Path David T. Nguyen10 Red: Nexus One default static configurations
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Outline Introduction Background Experimental Study Pilot Solution Evaluation David T. Nguyen11
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Approach Investigate impact of different storage configurations on power levels 1.Run series of benchmarks under default configurations 2.Repeat benchmarks under different configurations 3.Compare energy consumptions David T. Nguyen12
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Setup Rooted smartphone Nexus One 8 benchmarks Monsoon Power Monitor David T. Nguyen13
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Power Consumption: Default Config. (Queue Depth 128 / Write-back cache) David T. Nguyen14 Different algorithms - different power levels No algorithm optimal for all benchmarks Changing algorithms may save energy
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Power Consumption: Queue Depth 4 David T. Nguyen15 Shorter queue depth saves energy in most cases Not storage intensive benchmarks consume more power due to overhead of smaller queue
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Optimal Configurations Run benchmarks with all combinations of scheduling algorithms and queue depths Record in benchmark table David T. Nguyen16
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Outline Introduction Background Experimental Study Pilot Solution Evaluation David T. Nguyen17
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Big Idea Track phone’s run-time I/O pattern Match phone’s pattern with pattern from benchmark table Dynamically configure parameters with optimal savings David T. Nguyen18
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SmartStorage Architecture David T. Nguyen19
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GUI David T. Nguyen20
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I/O Pattern Matching David T. Nguyen21
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Outline Introduction Background Experimental Study Pilot Solution Evaluation David T. Nguyen22
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Energy Savings: Nexus One David T. Nguyen23
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Remaining Steps Energy savings with different caching policies / file systems / queue depths Matching using machine learning Adaptive I/O pattern recalculation Root reasons of energy savings David T. Nguyen24
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THANK YOU! David T. Nguyen25
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