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1 EE241 - Spring 2005 Advanced Digital Integrated Circuits Lecture 16: Ultra-Low Voltage Design 2 Minimum operational voltage of inverter Swanson, Meindl (April 1972) Further extended in Meindl (Oct 2000) Limitation: gain at midpoint > -1 Cfs: fast surface state capacitance Cox: gate capacitance Cd: diffusion capacitance For ideal MOSFET (60 mV/decade slope):
Transcript

1

EE241 - Spring 2005Advanced Digital Integrated Circuits

Lecture 16:Ultra-Low Voltage Design

2

Minimum operational voltage of inverter

Swanson, Meindl (April 1972)Further extended in Meindl (Oct 2000)

Limitation: gain at midpoint > -1

Cfs: fast surface state capacitanceCox: gate capacitanceCd: diffusion capacitance

For ideal MOSFET (60 mV/decade slope):

2

3

Confirmed by simulation (at 90 nm)Min Vdd (inverter)

0

10

20

30

40

50

60

70

80

90

100

0 0.5 1 1.5 2 2.5 3

pn ratio

mV

Source: Mircea Stan

Observe: non-symmetry of VTC increases Vddmin

For n =1.6,Vddmin = 1.9 UT= 48 mV

4

Also holds for more complex gates

Min Vdd (NOR)

0

20

40

60

80

100

120

0 0.5 1 1.5 2 2.5 3

pn ratio

mV

both inputs one input

Degradation due toasymmetry

3

5

Minimum energy per operation

Predicted by von Neumann: kTln(2)

Based on previous result – moving one electron over Vddmin:

Emin = QVDD/2 = q 2(ln2)kT/2q = kTln(2)

Would be approximately three times larger for CMOS inverter withPMOS twice the size of NMOS

At room temperature (300K): Emin = 0.29 10-20 J

Minimum sized CMOS inverter at 90 nm operating at 1VE = CVdd2 = 0.8 10-15 J, or 5 orders of magnitude larger!

6

Why Worry about Power?

Total Energy of Milky Way Galaxy: 1059 J

Minimum switching energy for digital gate (1 electron@100 mV): 1.6 10-20 J (limited by thermal noise)

Upper bound on number of digital operations: 6 1078

Operations/year performed by 1 billion 100 MOPS computers: 3 1024

Energy consumed in 180 years assuming a doubling of computational requirements every year.

4

7

Sub-threshold operation

After Vittoz (2005) (Piguet Low Power Electronics, Ch 16)

Basic equations:Leakage current (for Vgs = 0)

Saturation current:

Normalize all voltages to UT (= kT/q)

8

Minimum operation voltage of inverter

Voltages normalized to UT = kT/q

5

9

Minimum operation voltage of inverter

For VB > 4 UT • full logic swing• Leakage current approximately equal to I0

10

Dynamic Behavior

Propagation times normalized to T0 = CUT/I0Short circuit current ignorable if input rise time smaller

than T0

6

11

Propagation Delay

nxBDD

BexTT /0/ −==τ

12

Power and Power-Delay

Power:P = I0 VB + C VB

2 fα = duty factor = 2fTd = 2 Td / T (with T the clock period)

Power-Delay:

7

13

Power-Delay (Normalized)

For larger values of α, minimize the period T

14

Energy

Normalized Energy (over one period)

8

15

Optimal operational voltage

16

Example: Energy-Aware FFT

Wang, Chandrakasan, ISSCC 2004

9

17

18

FFT Energy-Performance Curves

10

19

Optimum Power Supply

20

Sizing Considerations (static)

Wn = 0.44 µm

11

21

Tiny XOR at 100 mV

22

Transmission Gate XOR

12

23

The Data-Retention Voltage (DRV) of SRAM

DRVV when , DD

inverterRight 2

1

inverterLeft 2

1 =∂∂=

∂∂

V

V

V

V

VDD

V1

M4

M3

M6M5

M2

M1

Leakagecurrent

V2

Leakagecurrent

VDDVDD

0 0

0 0.1 0.2 0.3 0.40

0.1

0.2

0.3

0.4

V1 (V)

2

VTC1VTC2

VDD=0.18V

VDD=0.4V

VTC of SRAM cell inverters

V2

(V)

When Vdd scales down to DRV, the Voltage Transfer Curves (VTC) of the internal inverters degrade to such a level that Static Noise Margin (SNM) of the SRAM cell reduces to zero.

DRV Condition:

Source: Huifang Qin

24

Impact of Each Transistor on DRVV

DD

M4

M3

M6

M5

M2

M1

VDD

VDD

00

V2 ≈ VDDV1 ≈ 0

VDD (V)

(V)

VDD

V2

V1

PMOS: 0.16u / 0.145uNMOS: 0.23u / 0.13uPass T: 0.16u / 0.16u

Without variation

NMOS leakage dominates

V2VDDV1

DRV

13

250 50 100 150 200 250 300

0

50

100

150

200

250

300

Simulated DRV of 1500 SRAM cells (mV)

His

togr

am o

f cel

l #

Monte-Carlo Simulation of DRV Distribution

Next: how to model the DRV distribution?

– I.e. compute the mean and variation of DRV given process variations.

26

Modeling SRAM DRV

• Coefficients extracted from transistor characterizations, such as Vthi, ni, I0i.

• E.g. a1=10mV, a2≈0, a3=-41mV, a4=11mV.

• This model can be used for DRV-aware SRAM design optimizations

DRV analytical model for any individual cell:

where DRV0 is from a variation-free SRAM cell at 27ºC

0 1 2 3 140 150 160 170 180 190

Transistor Width Scaling Factor

DR

V (

mV

)

M 1

M 3

M 4

Model

∑ ∑ ∆+∆+∆+=

∆+=

i ithii

ii TcVbaDRV

DRVDRVDRV

ββ

0

0

14

27

(V)

30mV

3mV

Impact of Each Transistor on DRVV

DD

M6

M5 V

DD

VDD

00

V2 ≈ VDD

V1 ≈ 0

VDD (V)

VDD

V2

V1

PMOS: 0.16u / 0.145uNMOS: 0.23u / 0.13uPass T: 0.16u / 0.16u

With variation

V2VDDV1

Due to the unbalanced P/N strength, State ‘1’preservation is vulnerable under low VDD.

P/N ratio and variations on state-holding transistors are critical for DRV

+

+–

DRV

28

DRV Sensitivities to Process Variations and T

0 1 2 3 4 5 6

50

100

150

200

250

Process variation ( σ )

DR

V In

crea

se (

mV

) T = 100 o C T = 27 o C

~100mV due to local process variation (3 σ )

~13mV due to temperature fluctuation

Process variation (∆L, ∆Vth) is the main factor that determines DRV

Chip temperature has weaker influence on DRV

-3 -2 -1 0 1 2 3-10

0

10

20

30

40

50

60

70

Process variation (σ)

DR

V in

crease

(m

v)

Vth loc var

L loc varVth glob var

L glob var

15

29

DRV and VDD Scaling Trend

Trend based on Berkeley Predictive Technology Model (BPTM)

Technology scaling brings crucial challenge to future low power SRAM operation stability

45 65 90 0

0.2

0.4

0.6

0.8

1

Technology node (nm)

Vol

tage

(V

)

DRV w/ perfect matching

DRV w/ 3σ process variation

V DD

Effective and innovative design techniques

30

SRAM Design for Lower DRV

100 200 300 4000

1000

2000

3000

4000

5000

6000

DRV (mV)

His

togr

am

of 3

2K S

RA

M c

ells

Solution I: ULV SRAM design optimization

SRAM Chip DRV

Solution II: Error-tolerant SRAM design (with Redundancy and ECC)

Optimized SRAM with ECC

16

31

130nm SRAM Sizing Impact on DRV

1

1.5

2

2.5

3

11.5

22.5

3110

120

130

140

150

160

170

180

190

βnβp

DR

V (

mV

)

11.2

1.41.6

1.82

2.2

11.2

1.41.6

1.82

2.2100

120

140

160

180

200

LnLp

DR

V (

mV

)

Ln=Lp=2.2

Ln=Lp=1

βn=3βp=1

βn=1βp=3

32

Measured DRV Spatial Distribution

• Measurement result of a 32k bit SRAM test chip

• Block boundary effect (row effect) is obvious.

17

33

SRAM Read/Write Sizing Issues

34

SubThreshold FFT

18

35

Operation at 180 mV

36

Energy Analysis

19

37

Is Sub-threshold the way to go?

Achieves lowest possible energy dissipation

But … at a dramatic cost in performance

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

0 0.2 0.4 0.6 0.8 1Vdd (V)

tp(u

s)

130 nm CMOS

38

Logic: Excessive Timing Variance

010

2030

4050

6070

80

0 0.2 0.4 0.6 0.8 1

Vdd (V)

σ/µ

(%)

Timing variance increases dramatically with Vdd reduction

Design for large yield means huge overhead at low voltages:Worst case design at 300mV means over 200% overkill

20

39

Power and timing trade-off’s

0

100

200

300

400

500

600

700

100 1000 10000 100000 1000000 10000000

Delay

Esw

Adaptive Tuning

Worst Case, w/o Vth tuning

Worst Case, w/ Vth tuning

Nominal, w/o Vth tuning

Nominal, w/ Vth tuning

40

Power and Timing Tradeoffs

5

10

15

20

25

30

35

40

45

50

1.0E+03 1.0E+04 1.0E+05 1.0E+06 1.0E+07

Path Delay (ps)

Esw

itch

ing

(fJ)

Worst Case, w/o Vth tuning

Nominal, w/o Vth tuning

Vdd: 200-500mV

21

41

ApproachesWorst-case design

Leaves too many crumbs on the table. Huge concurrency overhead for performance.

Self-timed or clockless designDefers the decisions to the system level. Comes with large overhead

Pseudo-synchronous design (e.g. Razor)

Allows for occasional timing errors. Limited operation range.

Self-adapting design.Turns on-line knobs (Vdd, Vt) to guarantee operation of the design. Uses one-time correction for systematic errors.

Operate at near-zero threshold voltages!

42

A Self-adapting Approach

Module

Motivation: Most timing variations are systematic, and can be adjusted forat start-up time using one-time calibration!

• Relevant parameters: Tclock, Vdd, Vth• Vth control — the most effective and efficient at low voltages• Can be easily extended to include leakage-reduction and power-down in standby

TestModule

Vdd

Vbb

Test inputsand responses

Tclock

• Achieves the maximum power saving under technology limit• Inherently improves the robustness of design timing• Minimum design overhead required over the traditional design methodology

22

43

Vth Tuning via Body Bias

Less design cost than Vdd tuning

Vth tunable range: >150mV for a 90nm Technology

0

0.1

0.2

0.3

0.4

0.5

0.6

-2 -1 0 1 2

Vth (V)

Vb

s(V

)

Reversed Vbs

Forward Vbs

G

B

S D

44

Power and Timing Tradeoffs

Vth tuning can effectively gain performance back

5

10

15

20

25

30

35

40

45

50

1.0E+03 1.0E+04 1.0E+05 1.0E+06 1.0E+07

Path Delay (ps)

Esw

itch

ing

(fJ)

Adaptive Tuning

Worst Case, w/o Vth tuning

Worst Case, w/ Vth tuning

Nominal, w/o Vth tuning

Nominal, w/ Vth tuning

Vdd: 200-500mV


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