Andrew B. Kahng
CSE and ECE Departments, UC San Diego abk@ucsd.edu
http://vlsicad.ucsd.edu/
Kahng ConFab-2015, 150521
1

•   Introduction: System Integration Roadmapping in ITRS2.0
•   Smartphone Driver: IoT (People)
•   Microserver Driver: IoT (Cloud)
•   IoT Driver: IoT (Things)
•   Summary
[source]   h+p://www.1.com/ww/en/internet_of_things/pdf/14-­‐09-­‐17-­‐IoTforCap.pdf
Kahng ConFab-2015, 150521
2

ORTCs
Fundamental  Models
INTC
PIDS
FEP
LITHO
I d,sat,
I sd,leak
CV/I,f
T
#cores,     max  IO  freq
Design  &
System  Drivers
#IOs,  max   power,  thermal,
TSV/3D  roadmap
•   max  chip  power
•   layout  density
•   transistor  count
•   chip  size
•   #disLnct  cores
•   #cores
•   max  on-­‐chip  freq
•   product/market   drivers
Test   A&P
Kahng ConFab-2015, 150521
3

Source: Internet of Things (IoT): A Vision, Architectural
Elements, and Future Directions, Future Generation Computer
Systems 29 (2013), pp. 1645-1660.
Kahng ConFab-2015, 150521
4

Source: Dr. P. Gargini, ITRS
Kahng ConFab-2015, 150521
5

•   Introduction: System Integration Roadmapping in ITRS2.0
•   Smartphone Driver: IoT (People)
•   Microserver Driver: IoT (Cloud)
•   IoT Driver: IoT (Things)
•   Summary
[source]   h+p://www.1.com/ww/en/internet_of_things/pdf/14-­‐09-­‐17-­‐IoTforCap.pdf
Kahng ConFab-2015, 150521
6

•
•
•   Products IN this class: iPhones and iPad
•   Products NOT IN this class: Snapdragon 810 / Apple A6
(processors instead of platforms), iWatch
•
•   Prominence of mobile, communication markets
•   Strict power budget with uncompromising performance
•   Drives heterogeneous integration of components and outside system connectivity
Kahng ConFab-2015, 150521
7

•   SOC-Consumer Portable (ITRS1.0 Driver) IC product evolves into ITRS 2.0 Smartphone Driver by adding additional components
Antenna
Switch
Receiver
Transceiver
NFC
BB/AP P
M
SOC-
CP
RF Tuner and
Demodulator
Audio   Bluetooth
Mul1-­‐mode   modem
Video   Wifi
SOC-CP (ITRS 2013)
Bio Sensor
Gyrometer
Kahng ConFab-2015, 150521
8

•
•   #AP cores
•   #GPU cores remains
•   MPU frequency
•
•   Form factor scaling
•   Display size scaling
•   Memory size and bandwidth scaling
•   Data communication bandwidth scaling
Kahng ConFab-2015, 150521
9

•   #AP cores
•   Platform complexity and performance
•   #GPU cores
•   Complexity and graphic performance
•   Max frequency (GHz)
•   Performance and power consumption
•   #MPixels of display
•   Graphic performance and system bandwidth
•   Mem BW (Gb/s)
•   Memory performance and system bandwidth
•   #Sensors
•   Peripheral diversity
•   #Antennas
•   Complexity of RF subsystem
•   #ICs
•   System complexity and BOM cost
•   Cellular data rate (MB/s)
•   Design requirement for RF subsystem and modem performance
•   WiFi data rate (Mb/s)
•   Design requirement for WiFi subsystem and modem performance
•   Board area (cm 2 )
•   System form factor
•   Board power (mW)
•   System power
Kahng ConFab-2015, 150521
10

BT BB x1
BT Transceiver x1
GSM
PA x1
RF Switch x1
SAW x3
Transceiver x1
VCO x1
TCXO x1
VGA Imaging Sensor x1
RF Connections Sensor
PMIC x1
DC-DC x2
Current Gauge x1
Analog Interface x1
BB Processor x1
Image Processor x1
LCD Driver x1
Display + Input devices
Power / Analog
AP / BB + Multimedia
4MB SDRAM x1
16MB NAND Flash x1
4MB NOR Flash x1
Memory
[Source: TechInsights]
Kahng ConFab-2015, 150521
11

BT + WiFi + FM BB x1
Connections
PMIC x1
Audio Amplifier x1
Power IC x8
RF
Multimode
PA x4
PA controller x1
GPS LNA x1
GSM+CDMA+WCDMA+GPS Transceiver x1
Antenna Switch
App Processor x1
Sensor
5M Imaging Sensor x1
VGA Imaging Sensor x1
Accelerometer x1
Flashlight Driver x1
Proximity Sensor x1
LCD Driver x1
Touchscreen Controller x1
Display + Input devices
Power / Analog
AP / BB + Multimedia
Notes:
1.
All multimedia features are on AP
2.
Audio output circuits integrated into one IC
3.
BT, WiFi, and FM (baseband) integrated into one IC
4.
Touchscreen introduced
5.
Memory scaling up
Memory
512MB DDR2 x1
4GB NAND Flash x1
Memory Controller x1
[Source: TechInsights]
Kahng ConFab-2015, 150521
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NFC
2x2 WLAN
BT4.1
Connections
Power Management
Platform
Power Management
Power / Analog
USB 3.0
Multimode
Low/Mid Band
PA/ Antenna
Switch Module
RxD Switch
High Band PA
Envelope Power Tracker
Diversity Antenna Tuner
RF
App Processor
Modem
GPU
LP Core
HP Core location
DRAM controller
DSP
Sensor engine
Dual ISP
Display engine
Multimedia
AP / BB + Multimedia
Sensor
Front Imaging Sensor
Back Imaging Sensor
Positioning Imaging Sensors
Environment
Sensor Complex
Gestures
LCD Driver
Touchscreen Controller
Display + Input devices
NAND Flash
Memory http://www.anandtech.com/show/7925/qualcomms-snapdragon-808810-20nm-highend-64bit-socs-with-ltecategory-67-support-in-2015
Kahng ConFab-2015, 150521
13

•   Market: computer vision, 2D-to-3D reconstruction
•   Multiple image sensors (e.g., Kindle Fire has four additional VGA sensors for 3D application)
•   Market: data mining of user behavior and HCI applications
•   Multiple sensors required to monitor environmental events
•   Aggressive power management with multiple sensors (e.g., Apple A7 use of co-processor as sensor hub)
•   Integration: MEMS integration (e.g., six-axes (gyro x accelerometer) in a package)
•   Block Diagram beyond 2015
•   Alt-1 (through 2019) has similar organization as smartphones in 2015 but integrates more sensors, sensor hub and antennas
•   Alt-2 (2020 and beyond) integrates several functions into the AP
•   System optimizations drive integrations and dis-integrations at SOC, SIP level [Sources]     h+p://www.techinsights.com/teardown.com/amazon-­‐fire-­‐phone/   h+p://www.invensense.com/mems/gyro/mpu6500.html
h+p://en.wikipedia.org/wiki/Apple_M7
Kahng ConFab-2015, 150521
14

BT + WiFi + FM BB
Connections
PMIC
Audio Amplifier
Power IC
RF
Multimode
PA
PA controller
GPS LNA
GSM+CDMA+WCDMA+GPS Transceiver
Antenna Switch
App Processor x1
Sensor
13M Imaging Sensor x1
2.1M Imaging Sensor x1
VGA Imaging Sensor x4
6 Axis Motion Sensor
Proximity Sensors
ALS
Temperature sensor
Sensor Hub
LCD Driver
Touchscreen Controller
AP / BB + Multimedia
Display + Input devices
Power / Analog
[Source]:
TechInsights
Amazon
Apple
Memory
DDR2
NAND Flash
Memory Controller
•   Similar organization as smartphones in 2014-2015
•   Integration of more sensors, antennas, sensor hub
Kahng ConFab-2015, 150521
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Multimode
RF
Multimode RF for 2G, 3G
LTE mm-Wave
BT
Wireless
XX (= voLTE, LTE-A, etc.)
Sensor
Front Imaging Sensor
Back Imaging Sensor
Positioning Imaging Sensors
Environment
Sensor Complex
XX (= Biometric, health, etc.)
Connections
PMIC
Audio Amplifier
Power IC
App Processor ( stacked )
Power / Analog
Core SDR
Baseband
LP cores
GPU
Core
AP / BB + Multimedia eDRAM LP cores
LCD Driver
Touchscreen Controller
Display + Input devices
Memory
NAND Flash
•   Multiple functions integrated into AP, e.g., heterogeneous memory, SDR BB
•   Integration of more sensors, antennas
•   SDR = Software-Defined Radio
Kahng ConFab-2015, 150521
16

20
15
#AP  cores
#AP cores = 1.0 * 1.14
(Year – 2007)
400
300
#GPU  cores
#GPU cores = 2.0 * 1.26
(Year – 2007)
10   200
5   100
0
2005   2010   2015   2020   2025   2030   2035
0
2005   2010   2015   2020   2025   2030   2035
8.0   Max  freq  (GHz)
6.0
Max freq = 2.3 * 1.04
(Year – 2011)
4.0
2.0
0.0
2005   2010   2015   2020   2025   2030   2035
•   #AP cores : This is the metric to evaluate AP performance and design complexity. More AP cores can also allow higher functionality integration. There will not be more co-processors for new features if AP cores can provide enough performance. (But low power requirement may be exception. For example, Apple M7.)
•   #GPU cores : This reflects the graphics processing capacity for 3D, holographic. Heterogeneous computing and programmability increases #GPU cores and other accelerators to be integrated with the GPU cores. Beyond 2019, context-based computing will drive #cores for both AP and GPUs
•   Max freq : Linear growth of 4% per year due to power constraints. In 2029, the max power is ~12W, which will drive low-power design methodologies
Kahng ConFab-2015, 150521
17

30
#Sensors
20
#Antennas
20
10
#Sensors = 7 + (Year – 2009) * 0.85
0
2005   2010   2015   2020   2025   2030   2035
10
#Antennas = 7 + (Year – 2009) * 0.4
0
2005   2010   2015   2020   2025   2030   2035
15.0
#ICs
10.0
5.0
#ICs = 10 - (Year – 2009) * 0.15
0.0
2005   2010   2015   2020   2025   2030   2035
•   Sensors: Diverse sensors such as environment/ambience, accelerometers, health, vibration till 2019.These grow due to proliferation of IoT, context-based computing, pressure, gyro, acoustic, light, etc. However, beyond 2013 the number of sensors saturate due to the form factor limitations of a smartphone.
•   Antennas: Diverse antennas for WiF, BT, and cellular. The diversity is driven by WiFi standards (e.g., 802.11ac, ad, etc.) and cellular (e.g., LTE-Advanced, TD-LTE, VoLTE). IoT and context-based computing will push WiFi and cellular standards and their BW requirements. Beyond 2021, the number of antennas saturate but standard evolve and increase the bandwidth.
•   #ICs: There is an increase and then decrease due to integration and deintegration of functions (e.g., PEs, sensor hubs, antennas)
Kahng ConFab-2015, 150521
18

40.0
30.0
20.0
10.0
#MPixels
#MPixels = 0.7 * 1.27
(Year – 2013)
0.0
2005   2010   2015   2020   2025   2030   2035
600000.0
500000.0
400000.0
300000.0
Mem  BW  (Mb/s)
After calibration with 2014 data point
Mem BW = 136000 * 1.09
(Year – 2014) ; Year > 2014
200000.0
100000.0
0.0
2005   2010   2015   2020   2025   2030   2035
•   #MPixels: Display pixels driven by high-definition standards (e.g., 720p, 1080p, 4K). #bits per pixel and refresh rates do not scale per year significantly (e.g., #bits per pixel limited to 64bits and refresh rate limited to 120Hz, 240Hz for 3D). Large display sizes drive up memory BW requirements. By 2029, super HD resolutions of 7680 x 4320 will increase memory BW requirements to 144Gb/s [ http:// en.wikipedia.org/wiki/Ultra_high_definition_television ]
•   Mem BW: This is defined as the BW between AP and off-chip DRAMs. This reflects the requirement for memory integration technologies. Higher mem BW is due to advanced WiFi, cellular standards, display frame rates and evolution of context-based computing and on-body sensors that’ll require user-specific information to be stored and retrieved when the user’s environment changes. In 2029, the memory BW is 525Gb/s to support super HD display frame rates. The energy consumption till 2019 is ~25pJ/bit and after that around 10pJ/bit with optical interconnects/on-chip plasmonics [ https://www.cs.ucsb.edu/~sherwood/pubs/JETCAS-12plasmon.pdf
], which is ~5.3W for 525Gb/s memory BW. This is larger than total smartphone max power (~4W). Therefore, aggressive memory power management techniques will be needed to reduce this power.
Kahng ConFab-2015, 150521
19

•   Introduction: System Integration Roadmapping in ITRS2.0
•   Smartphone Driver: IoT (People)
•   Microserver Driver: IoT (Cloud)
•   IoT Driver: IoT (Things)
•   Summary
[source]   h+p://www.1.com/ww/en/internet_of_things/pdf/14-­‐09-­‐17-­‐IoTforCap.pdf
Kahng ConFab-2015, 150521
20

•
•   Products is IN this class: HP Moonshot, HP ProLiant servers
•   Products NOT IN this class: Intel Atom processor (not a platform)
•
•   Demand for low-latency data processing
•   Demand to reduce CO
2
emission and cooling expenses by improving datacenter power efficiency
•   Realization of warehouse computer paradigm
Kahng ConFab-2015, 150521
21

•   MPU-HP (high-performance MPU IC driver) is incorporated into the microserver (ultimately, server / datacenter) System Driver core1 core1 core1 core1 core2 core2 core3 core2 core2 core4 core3 core3
SRAM1
SRAM1 core3 core4 core4
SRAM1
SRAM1
SRAM2
SRAM2
SRAM3 core4
U n c o c o
U n re
SRAM3
SRAM3
SRAM3
SRAM4
SRAM4
SRAM4 c o
U n re   c o
U n re
4 × MPU-HP (ITRS 2013)
HP ProLiant Microserver with
16 cores
•   Metrics evolved from MPU-HP in ITRS 1.0
•   MPU frequency, logic/SRAM breakdown, #cores, …
•   New metrics added to account for network / backplane bandwidth, storage capacity, …
Kahng ConFab-2015, 150521
22

•
•   Density of cartridges
•
•   Performance
•
•   Local memory capacity
•
•   Intra-node system bandwidth
•
•   Inter-node system bandwidth
•
•   Per-node performance
Kahng ConFab-2015, 150521
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MPU-­‐0
Memory
Controller
Cores
PCIe  2.0
×  8
10.7GB/s
DDR3
2GB/s
1GB/s
Local  SATA
Drives
GbE  ×  2
1GB/s
Peripherals
[source]   h+p://h20195.www2.hp.com/v2/GetDocument.aspx?docname=4AA5-­‐0893ENW&doctype=data%20sheet&doclang=EN_US&searchquery=&cc=us&lc=en   h+p://www.intel.com/content/dam/www/public/us/en/documents/datasheets/atom-­‐processor-­‐s1200-­‐datasheet-­‐vol-­‐1.pdf
h+p://en.wikipedia.org/wiki/List_of_device_bit_rates
Kahng ConFab-2015, 150521
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MPU-­‐0
10.7GB/s
Microserver revolution – since 2012
Memory
Controller
DDR3
Compared to conventional server:
1.
2.
Few (
Cores
Significant reduction of MPU performance (2.0GHz) and system-level bandwidth
(PCIe
≤
×
4) MPU per server cartridge
8)
3.
PCIe hub is integrated into MPU
4.
No auxiliary chipset
-- BOM cost and integration effort are reduced
5.
Inexpensive components
-- SAS à SATA
-- Buffered DDR3 à Unbuffered DDR3
1GB/s
1GB/s
GbE  ×  2
Peripherals
[source]   h+p://h20195.www2.hp.com/v2/GetDocument.aspx?docname=4AA5-­‐0893ENW&doctype=data%20sheet&doclang=EN_US&searchquery=&cc=us&lc=en   h+p://www.intel.com/content/dam/www/public/us/en/documents/datasheets/atom-­‐processor-­‐s1200-­‐datasheet-­‐vol-­‐1.pdf
h+p://en.wikipedia.org/wiki/List_of_device_bit_rates
Kahng ConFab-2015, 150521
25

MPU-­‐0
Cores   Cores   Cores
Memory
Controller
Low  power   cores
Low  power   cores
Low  power   cores
Accelerator Accelerator
Electrical
Interconnects
(PCIe  3.x)   eDRAM
Op1cal
Interface
DRAM
Op1cal
Networks
•   Introduction of optical interconnects, mainstream heterogeneous cores
Local  Drives
Peripherals
“22-nm Next-Generation IBM System z Microprocessor”, ISSCC 2015 (proof point for eDRAM and memory controller integration in cores)
Kahng ConFab-2015, 150521
26

•   Computational power density challenges may imply SOC/ASIClike trajectories
•   More light cores
•   More peripherals
•   More application-specific accelerators
•   More complicated inter-IP communication fabrics
•   Higher integrated network bandwidth to address system throughput requirements under strict form-factor and power constraints
•   Block Diagram beyond 2015
•   Alt-1 (through 2019) has similar organization as microservers in
2014/2015 with architectural improvements in MPUs and peripherals
•   Alt-2 (2020 and beyond) integrates optical interconnects and heterogeneous cores
Kahng ConFab-2015, 150521
27

MPU-­‐0
Cores   Cores   Cores
Memory
Controller
Cores   Cores   Cores
Accelerator Accelerator
Local  SATA  (or
XX)  Drives
DDRXX
PCIe  XX  Hubs
Op1cal
Interface
Op1cal
Networks
•   Similar organization as microservers in
2014/2015
•   Architectural improvements in components, e.g., PCIe, DRAM, cores, etc.
•   Timeline is beyond 2015, but up to 2019
Peripherals
Kahng ConFab-2015, 150521
28

MPU-­‐0
Cores   Cores   Cores
Memory
Controller
Low  power   cores
Low  power   cores
Low  power   cores   eDRAM
Accelerator Accelerator
Hub  for  op1cal
Electrical
Interconnects
Fiber  Interface
DRAM  +
Op1cal   storage
Op1cal
Networks
•   Introduction of on-chip optical interconnects, mainstream heterogeneous cores
•   Timeline is from 2020 and beyond
Local  Drives
Peripherals
Kahng ConFab-2015, 150521
29

180
160
140
120
100
80
60
#MPU  cores  /  rack  unit
#MPU cores/rack unit
= 16 * 1.19
(Year – 2013) ; Year ≤ 2019
= 45 * 1.12
(Year – 2019) ; Year > 2019
40
20
0
2009   2011   2013   2015   2017   2019   2021   2023   2025   2027   2029
7
Max  frequency  (GHz)
6   Max freq = 3.46 * 1.04
(Year – 2013)
5
4
3
Follows MPU-HP/
CP trajectory
2
1
Performance challenge, might need better processor / memory architecture
0
2009   2011   2013   2015   2017   2019   2021   2023   2025   2027   2029
MPU  frequency  x  #Core  (GHz)  /  rack  unit
1200
1000
800
600
#MPU cores/rack unit
= 55 * 1.24
= 45 * 1.16
(Year – 2013)
(Year – 2019)
; Year ≤ 2019
; Year > 2019
400
200
0
2009   2011   2013   2015   2017   2019   2021   2023   2025   2027   2029
•   These metrics are driven by the max power delivery to a rack. Most of the jobs on microservers are batch-processed, which drives the number of low-power cores grow in the roadmap. The growth is constrained by power and cost.
•   The frequency roadmap is same as the existing MPU-CP roadmap and driven by real-time jobs (e.g., video streaming, maps, virtualization) [ http://forums.whirlpool.net.au/archive/2234398 ]. The roadmap is limited by power, which grows to ~90W in
2029 and will drive low-power design methodologies.
Kahng ConFab-2015, 150521
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DRAM  capacity  /  rack  unit  (GB)
1000000
100000
10000
1000
100
10
1
2010   2015
DRAM / Rack Unit (GB)
= 128 * 1.58
(Year – 2013)
2020   2025   2030
DRAM  BW  (GB/s)
3000
2500   DRAM BW
= 51.2 * 1.26
(Year – 2013)
2000
1500
1000
500
Grows as #cores increase per rack
0
2009   2011   2013   2015   2017   2019   2021   2023   2025   2027   2029
Off-­‐MPU  BW  (GB/s)
900
800
700
600
500
400
300
200
100
0
2009
Off-MPU BW
= 32 * 1.28
(Year – 2013) ; Year ≤ 2019
= 144 * 1.18
(Year – 2019) ; Year > 2019
2014   2019   2024   2029   2034
•   DRAM cap per rack unit is driven by the number of cores in a rack and redundancy due to using advanced RAID [ http://www.newegg.com/Product/
Product.aspx?Item=N82E16859107052 ] and cloud data storage needs
•   IBM expects 2TB / 1U in 2019 [https://www.power.org/wp-content/uploads/2012/10/15.-IBM-DB2_lui-v5.pdf]
•   DRAM BW is driven by faster clocks, the number of cores and smaller latency requirements for high-priority tasks (e.g., ads, maps) [ http:// www.theregister.co.uk/2013/09/04/intel_avoton_rangeley_atom_c2000 ]
•   Off-MPU BW is driven by both batch and real-time applications (e.g., queries, video streaming)
Kahng ConFab-2015, 150521
31

•   Introduction: System Integration Roadmapping in ITRS2.0
•   Smartphone Driver: IoT (People)
•   Microserver Driver: IoT (Cloud)
•   IoT Driver: IoT (Things)
•   Summary
[source]   h+p://www.1.com/ww/en/internet_of_things/pdf/14-­‐09-­‐17-­‐IoTforCap.pdf
Kahng ConFab-2015, 150521
32

•   IoT (Things) are extremely compact, low-power MCU platforms with sensors which can be ubiquitously deployed in the environment
•   Product (research) IN this class: Smart Dust; Nest
•   Products NOT IN this class: MEMS chip, MCU, proximity sensors
•   Why a System Driver
•   Drives display market (huge number of devices to be deployed)
•   Drives robust reliability and battery requirements to work under harsh environmental conditions
•   Drives extremely low suspend power requirement
•   Increasing performance requirement
•   Drives heterogeneous integration and connectivity requirements
(packaging, interconnect, panel technologies)
Kahng ConFab-2015, 150521
33

•
[Source]   h+p://www.1.com/ww/en/internet_of_things/pdf/14-­‐09-­‐17-­‐IoTforCap.pdf
Kahng ConFab-2015, 150521
34

•   Power à sufficient lifetime without battery replacement
•
•
•
Lowest  system  supply  voltage  (V)
Ba+ery  capacity  (mA-­‐h)
Deep  suspend  current  (nA)
•
•
•
DC-­‐DC  efficiency  (%)
DC-­‐DC  power  density  (W/mm^2)
Peak  Tx/Rx  current  (mA)
•   Performance à sufficient computation capacity for applications
•   MCU  #Cores
•   MCU  #FPUs
•   MCU  IDD  /  Opera1on  frequency  (uA/MHz)
•   Max  MCU  Frequency  (MHz)
•   MCU  SRAM  Size  (KB)
•   MCU  Flash  Size  (KB)
•   MCU  MIPS
•   Form factor à small system size to simplify deployment
•   MCU  Package  size  (mm^2)
•   Peripheral à sufficient interfaces to interact with physical world
•   #Integrated  Comm.  Protocols  of  MCU
•   #  of  MCU  GPIOs
•   #ADC  channels
•   ADC  resolu1ons
•   #PWM
•   Reliability à robustness under harsh environment
•   Life1me  #access  of  NVM  memory
•   Device  life1me  (years)
•   Max  system  supply  voltage  (V)
Kahng ConFab-2015, 150521
35

•   Potential new device, interconnect roadmaps
•   Very low duty cycle to reduce the lifetime energy consumption
•   Fine-grained power modes to adapt to application contexts
•   Potential new integration technologies
•   Complex communication protocols, large bandwidth requirements
•   Heterogeneous integration in stacked ICs
(WAS) (IS) h+p://cache.freescale.com/files/microcontrollers/doc/brochure/
BRLWPWR.pdf
Kahng ConFab-2015, 150521
36

•   IoT SOCs require on-chip NVM for storing programs and data
à new NVM technology to dominate [1]
•   Fin discreteness à integrated RF, analog circuits may favor
FD-SOI over FinFET, unlike pure logic devices [2]
STM  technology  roadmap  for  IoT  SOC [2]
Comparison  of  process  integra1on  between   floa1ng  gate  and  SONOS [1]
[1]   h+p://www.cypress.com/?docID=45736
[2]   h+p://www.ee1mes.com/document.asp?doc_id=1325866&
Kahng ConFab-2015, 150521
37

•   Assumption: energy harvesting introduced in 2017
•   Lowest supply voltages drops significantly
•   Deep suspend current reaches ~10nA level concurrent with deployment of energy harvesting
Lowest  system  supply  voltage
(energy  source)  (V)
2
1.5
1
0.5
0
2014   2016   2018   2020   2022   2024   2026   2028   2030
Deep  suspend  current  (nA)
120
100
80
60
40
20
0
2014   2016   2018   2020   2022   2024   2026   2028   2030
[source]     h+p://eh-­‐network.org/files/human_power.pdf
h+p://www.cymbet.com/pdfs/Powering-­‐Wearable-­‐Technology-­‐and-­‐the-­‐Internet-­‐of-­‐Everything-­‐WP-­‐72-­‐10.1.pdf
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•   Data from published articles, product datasheets
•   Driven by low-power requirement
1.00
0.80
0.60
0.40
1.20
DC-­‐DC  efficiency  (%)
0.20
0.00
2014   2016   2018   2020   2022   2024   2026   2028   2030
DC-­‐DC  power  density  (W/mm^2)
3.50
3.00
2.50
2.00
1.50
1.00
0.50
0.00
2014   2016   2018   2020   2022   2024   2026   2028   2030
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•   Power consumed by connectivity is critical to IoT
•   High peak currents inconsistent with small battery size, energy harvesting
•   Improved system-level power efficiencies expected (e.g., “do nothing well”)
Peak  Tx/Rx  current  (mA)
Tx/Rx  power  per  bit  (uW/bit)
60.00
3.00
50.00
2.50
40.00
2.00
30.00
1.50
20.00
1.00
10.00
0.50
0.00
2014   2016   2018   2020   2022   2024   2026   2028   2030
0.00
2014   2016   2018   2020   2022   2024   2026   2028   2030
Power overhead (normalized to BW)
= (energy per bit in uJ) / (bit/sec)
= uW/bit
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•   System form factor is limited (e.g., by battery technology) in near term
•   After 2017, form factor scales as devices go to 3D / 2.5D or better analogdigital system partitioning, integration
•   Scaling of passives (number, size) eventually blocks form factor scaling
à novel solutions needed
Module  footprint  (mm^2)
45.00
40.00
35.00
30.00
25.00
20.00
15.00
10.00
5.00
0.00
2014   2016   2018   2020   2022   2024   2026   2028   2030
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•   Introduction: System Integration Roadmapping in ITRS2.0
•   Smartphone Driver: IoT (People)
•   Microserver Driver: IoT (Cloud)
•   IoT Driver: IoT (Things)
•   Summary
[source]   h+p://www.1.com/ww/en/internet_of_things/pdf/14-­‐09-­‐17-­‐IoTforCap.pdf
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•   IoT (Things) still a developing product category
•   New applications, drivers and integration challenges are expected
•   Not-yet-roadmapped applications
•   Automobile electronics (ADAS, transportation management, selfdriving car)
•   Smart electronics (wearables, etc.) + implied big data applications
[Source]
R.  Aschenbrenner,  “Hetero-­‐integra1on  for  cyber  physical  systems  at  wafer-­‐level  and  panel-­‐level”,  INC-­‐11,  2015.
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•   Example: Roadmap for computer vision support
•   Middle 200X à RFID tags/facilitating routing = barcode scanning
•   Early 201X à gesture detection
•   Early 201X à transport = license plate detection
•   Middle 201X à locating people = face recognition
•   Late 201X à ubiquitous positioning = (highly sensitive) security/surveillance
•   Early 202X à physical-world web = realtime, high resolution machine vision
[source]   h+p://en.wikipedia.org/wiki/Internet_of_Things#/media/File:Internet_of_Things.png
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•   ITRS 2.0 System Integration Focus Team : roadmaps of system drivers that drive semiconductor and design technologies
•   Initial proofs of concept (2014): Smartphone, Microserver
•   2015 target: “IoT (Things)”
•   Roadmapping process based on calibration data (product teardowns and physical analyses, product datasheets), block diagram evolution, extrapolation
•   Key interactions in ITRS 2.0 with Heterogeneous Integration and Outside System Connectivity
•   Your feedback and inputs, contributions welcome!
My email: abk@ucsd.edu
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•   Dr. Juan-Antonio Carballo, Dr. Paolo Gargini
•   ITRS 2.0 System Integration Focus Team
•   Wei-Ting Jonas Chan, Siddhartha Nath and other UCSD
VLSI CAD Laboratory members
•   Recent publications:
•   J.-A. Carballo, W.-T. J. Chan, P. A. Gargini, A. B. Kahng and S. Nath,
"ITRS 2.0: Toward a Re-Framing of the Semiconductor Technology
Roadmap", Proc. ICCD , 2014, pp. 139-146.
•   W.-T. J. Chan, A. B. Kahng, S. Nath and I. Yamamoto, "The ITRS MPU and SOC System Drivers: Calibration and Implications for Design-Based
Equivalent Scaling in the Roadmap", Proc. ICCD , 2014, pp. 153-160.
•   “ITRS 2.0: Top-Down System Integration” http://semimd.com/blog/2015/04/22/itrs-2-0-top-down-system-integration/
•   A. B. Kahng, "The Road Ahead: Predicting the future of information technology and society", IEEE Design and Test , Nov-Dec 2012, pp.
101-102.
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•   Performance: required Mpixel/sec for CV applications
•   Power efficiency: nJ/pixel (characterized from FPGA + mobile SOC CV [1])
•   At < 0.1W, severe power challenges for CV applications on IoT/wearable devices à technology and system architecture solutions needed
500
Required  Mpixel/sec  (data  point)
400
300
Required  Mpixel/sec  (est.)
200
100
0
2005   2010   2015   2020   2025   2030   2035
100
Power  (W)
10
Power constraint ~0.1W
(from ARM roadmap)
1
2005   2010   2015   2020   2025   2030   2035
Year
Resolu1on
FPS
Required  Mpixel/sec
(data  point)
Required  Mpixel/sec
(est.)
Energy  per  pixel  (nJ)
Power  (W)
2008   2009   2010   2011   2012   2013   2014   2015   2016   2017   2018   2019   2020   2021   2022   2023   2024   2025   2026   2027   2028   2029
QVGA       VGA
5       15
VGA
30
HD720
30
HD1080
30
VGA
240
0.4
0
1
5
5
6
8
10
13
231
3
9
16
231
4
20
231
5
25
231
6
28
31
231
7
40
231
9
62
50
231
12
63
231
14
79
231
18
73
99
231
23
125
231
29
158
231
36
198
231
46
249
231
58
314
231
72
395
231
91
[1]  h+p://www.inf.ethz.ch/personal/pomarc/pubs/HoneggerIROS14.pdf
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