non volatile main memory for handheld devices: an - ashok… · varun gohil, shreyas singh, sneha...
TRANSCRIPT
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Non Volatile Main Memory for Handheld Devices: An
idea whose time has come
Manu Awasthi
Associate Professor
Ashoka University
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Handheld Devices
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Android Versions
System software is evolving rapidly : Android has 1 release / yearhttps://www.counterpointresearch.com/can-android-o-de-fragment-android/
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Memory Capacity : Individual Usage
Applications are becoming feature rich, with increasing memory capacity requirements
https://eitik.com/17-android-browser-tested-for-memory-usage-in-2018/
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Memory Capacity : Individual Usage
https://www.androidauthority.com/how-much-ram-do-you-need-in-smartphone-2019-944920/
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Market Trends : Memory Capacity17X
Increase
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Energy Consumption
Domain Knowledge Based Energy Management in Handhelds, Nachiappan et al. HPCA 2015
Skype MP Game
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Summary of Trends
• Handheld applications are becoming complex and feature rich• Larger working sets• Much higher bandwidth capacity needs, especially when
multiprogramming
• Memory sub systems can consume less energy• Fraction of energy consumed by memory subsystem is growing
Both are (somewhat) contradictory goals
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Non Volatile Memory Technologies
9
• Been around since 1960s, renewed interest with the projected decline of DRAM
• Many candidates : Phase Change Memory (PCM), Spin-Torque Transfer Memory (STT-RAM), 3D-Xpoint, Resistive RAM (ReRAM) etc.
• Vary based on underlying mechanism for storing information
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Non Volatile Memories+ Many candidates: PCM, STT-MRAM, others
+ Higher areal density : 2x – 4x compared to DRAM
+ Lower access energies
+ No Refresh
- Higher access latencies
- Asymmetric read / write energies
- Reduced endurance
A Survey of Software Techniques for Using Non-Volatile Memories for Storage and Main Memory Systems, Mittal et al., IEEE TPDS 201610
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PCM Primer
PCM is resistive memory: High resistance (0), Low resistance (1)PCM cell can be switched between states reliably and quickly
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PCM Working Example• Write: change phase via current injection
• SET: sustained current to heat cell above Tcryst
• RESET: cell heated above T
melt and quenched
• Read: detect phase via material resistance
LargeCurrent
SET (cryst)Low resistance
103-104 Ω
SmallCurrent
RESET (amorph)High resistance
AccessDevice
MemoryElement
106-107 ΩSlide Courtesy: Moinuddin Qureshi, IBM
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Mobile Architecture Research● Mobile computing research: 1% of research papers published each
focus on mobile computing.
● Lack of tools
V. J. Reddi, H. Yoon, and A. Knies, “Two billion devices and counting,” IEEE Micro, vol. 38, no. 1, pp. 6–21, January/February 2018.
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What is needed?
• Tool and Simulators
• Benchmarks
BBench(Michigan)
AsimBench(ICT, China)
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Current Status
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Android Emulator
Android Open Source Project (AOSP)
Android Virtual Device (AVD)
Android Emulator
Device Behavior
How do we leverage the existing ecosystem to study memory behavior of Android apps?
• Can boot multiple Android versions, apps
• Multiple device types
• Provides functional model, need analysis wrappers
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META: Tool Design
MobiCom 2018
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Raw Traces
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Cache Simulation Module
Cache hierarchy specification
L1/L2 Cache hit rates: Calculator App Android 4 (Kitkat) to Android 7 (Nougat).
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Main Memory Simulation Module : NVMain
• NVMain : cycle-level main memory simulator
• Can simulate DRAM, emerging NVMs
• DRAM variants : LPDDRx, DDRx• Emerging memory technologies:
PCM, STT-RAM etc.
• Statistics on memory latencies, bandwidth, utilizations etc.
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META : Potential Use Cases
• Trace Generation• The traces can also be used to analyze instruction distribution profile.• Creation of synthetic inputs to models based on real instruction profiles
• Cache Hierarchy Modeling• A custom, N-level cache hierarchy
• DRAM, Non-volatile, Hybrid Memory Simulation• NVMain can model most technologies
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Trends in Handheld Devices
22
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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Requirements of Handheld Devices
• Response Time• Most devices are for information consumption• Delays will hinder user engagement
• Energy Efficiency • Battery life is of paramount importance
• Increased need for memory capacity
• NVM Technologies cannot be used as is : Need architectural exploration of characteristic comparisons
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Main Memory in Handhelds
24
MC
Core 1 Core 2
Core 3Core 4
Fabric Fabric
GPU
Camera
Display
Audio
Sensors
Modem
DRAM DRAM
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Handheld Applications
25
If frequently accessed data can be concentrated to the fastest regions of a hybrid memory hierarchy, memory
system’s energy consumption can be reduced significantly, without any significant loss in performance and user
experience.
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Hybrid Memory Architectures for Handhelds
Total Physical Address Space
0 GB 4 GB
Sub Address Space Sub Address Space Sub Address Space
DRAMMem
Tech 2NVM
DATE 2018
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Hybrid Main Memory in Handhelds
2727
MC
Core 1 Core 2
Core 3Core 4
Fabric Fabric
GPU
Camera
Display
Audio
Sensors
Modem
DRAM NVM
MC
DATE 2018
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Hybrid Main Memory in Handhelds
28
MC
Core 1 Core 2
Core 3Core 4
Fabric Fabric
GPU
Camera
Display
Audio
Sensors
Modem
DRAM
NVM
MC MC MC
NVM
DRAM
DATE 2018
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Results
29
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Summary and Key Takeaways• Research in architectures of handheld devices architectures is
important more so in the era of wearables• Memory sub-system is becoming increasingly important, even in
handheld• Need tools, benchmarks to carry research forward• META – one step in that direction
• NVMs should be integrated into handheld memory hierarchy• Mechanisms to provide access to high capacity, low latency
memories might require intelligent data management• H/W – S/W co-design is better than one or the other
30
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Acknowledgements
Varun Gohil, Shreyas Singh, Sneha Ved (IIT Gandhinagar)
Nisarg Parikh (LD College of Engineering)
Sarabjeet Singh (Ashoka University)