handheld device architectures: are we doing...
TRANSCRIPT
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HandheldDeviceArchitectures:AreWeDoingEnough?
ManuAwasthiAshokaUniversity
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HandheldDevices
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AndroidVersions
https://www.counterpointresearch.com/can-android-o-de-fragment-android/
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MemoryUsage
https://eitik.com/17-android-browser-tested-for-memory-usage-in-2018/
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AFewTrends
5
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MobileArchitectureResearch● Mobile computing research: 1% of research papers published eachfocus on mobile computing.
● Lack of tools
V.J.Reddi,H.Yoon,andA.Knies,“Twobilliondevicesandcounting,”IEEEMicro,vol.38,no.1,pp.6–21,January/February2018.
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Whatisneeded?
• ToolandSimulators
• Benchmarks
BBench(Michigan)
AsimBench(ICT,China)
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CurrentStatus
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AndroidEmulator
AndroidOpenSourceProject(AOSP)
AndroidVirtualDevice(AVD)
AndroidEmulatorDeviceBehavior
HowdoweleveragetheexistingecosystemtostudymemorybehaviorofAndroidapps?
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META:ToolDesign
MobiCom2018
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TracerModule- ModificationsinQEMU
ModifiedTranslationPath
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RawTraces
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META:ToolDesign :CacheModule
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CacheSimulationModule
L1andL2CachehitratesavailableafterrunningacalculatoronarangeofandroidversionsfromAndroid4(Kitkat)toAndroid7(Nougat).
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META:ToolDesign:MemoryModule
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NVMainIntegration
● NVMain :cycle-levelmainmemorysimulator
● CansimulateDRAM,emergingnon-volatilememoriesatthearchitecturallevel.○ Phasechangememory,STT-RAM
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PotentialUse-cases
● TraceGeneration○ Thetracescanalsobeusedtoanalyzeinstructiondistributionprofile.○ Creationofsyntheticinputstomodelsbasedonrealinstructionprofiles
● CacheHierarchyModeling○ Acustom, N-levelcachehierarchy
● DRAM,Non-volatile,HybridMemorySimulation○ NVMain canmodelmosttechnologies
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TrendsinHandheldDevices
18
https://thehackernews.com/2015/09/6gb-ram-smartphone.html
http://www.es.ele.tue.nl/~kgoossens/Chandrasekar14PHD.pdfhttps://www.pwc.com/gx/en/technology/mobile-innovation/assets/pwc-dram-memory.pdf
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HandheldsandSmartphones
19HexagonDSP:AnArchitectureOptimizedforMobileMultimediaandCommunications,IEEEMicro,Vol34,2014
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MainMemoryinHandhelds
2020
MC
Core1 Core2
Core3Core4
Fabric Fabric
GPU
Camera
Display
Audio
Sensors
Modem
DRAM DRAM
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HandheldApplications
21
Iffrequentlyaccesseddatacanbeconcentratedtothefastestregionsofahybridmemoryhierarchy,memory
system’senergyconsumptioncanbereducedsignificantly,without anysignificantlossinperformanceanduser
experience.
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HybridMemoryArchitecturesforHandhelds
TotalPhysicalAddressSpace0GB 4GB
SubAddressSpace SubAddressSpace SubAddressSpace
DRAMMemTech2NVM
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HybridMainMemoryinHandhelds
2323
MC
Core1 Core2
Core3Core4
Fabric Fabric
GPU
Camera
Display
Audio
Sensors
Modem
DRAM NVM
MC
DATE2018
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HybridMainMemoryinHandhelds
24
MC
Core1 Core2
Core3Core4
Fabric Fabric
GPU
Camera
Display
Audio
Sensors
Modem
DRAM
NVM
MC MC MC
NVM
DRAM
DATE2018
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Results
25
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Results– 4Controllers
26
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KeyTakeways
• Researchintohandhelddevicesarchitecturesisimportant,moresointheeraofwearables• Memorysub-systemisbecomingincreasinglyimportant,eveninhandheld• Needtools,benchmarkstocarryresearchforward• META– onestepinthatdirection
• NVMswilleventuallybeintegratedintomemoryhierarchy• Mechanismstoprovideaccesstohighcapacity,lowlatencymemoriesmightrequireintelligentdatamanagement• H/W– S/Wco-designisbetterthanoneortheother.
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Acknowledgements
VarunGohil,Sneha Ved (IITGandhinagar)
NisargParikh(LDCollegeofEngineering)