dynamic voltage and frequency scaling · etienne le sueur and gernot heiser dynamic voltage and...

Etienne Le Sueur and Gernot Heiser

Dynamic Voltage and Frequency ScalingThe Laws of Diminishing Returns

HotPower’10, Vancouver, Canada, [email protected]

mailto:[email protected]

mailto:[email protected]

© NICTA 2010 www.ertos.nicta.com.au/research/power/ /35

What is DVFS?

Dynamic Voltage and Frequency Scaling

2

http://www.ertos.nicta.com.au/research/power/


P = CfV 2


What is DVFS?

3



P = CfV 2


What is DVFS?

dynamic power consumption

3



P = CfV 2


What is DVFS?


constant

3



P = CfV 2


What is DVFS?


frequencyconstant

3



P = CfV 2


What is DVFS?

dynamic power consumption voltage squared

frequencyconstant

3




In the past...

“Under some conditions, we observe energy savings of 30% for a 4% performance loss.”

Snowdon et al. [2009]

4




In the past...

“... in most of the traces the potential for energy savings is good. The savings range from about 5% to about 75%, with most data points falling between 25% to 65% savings.”

Weiser et al. [1994]

5




In the past...

“Energy savings of 22% ... to complete the same task are possible without a substantial reduction in application performance...”

Weissel et al. [2002]

6




In the past...

“... Hence, on this system, by lowering the frequency to a point where the workloads can be adequately served without sacrificing latency, energy is saved.”

Miyoshi et al. [2002]

7



P = CfV 2 + Pstatic


The whole story

8



P = CfV 2 + Pstatic


The whole story

total power consumption

8



P = CfV 2 + Pstatic


The whole story



8



P = CfV 2 + Pstatic


The whole story



static power consumption

8




Static power consumption

9





9

CPU leakage





9

Hard drives

CPU leakage





9

Hard drives

CPU leakage

Memory





9

Hard drives

CPU leakage

Memory

Power supply losses





9

Hard drives

CPU leakage

Memory

etc.Power supply losses




How can DVFS save energy?

400c30: 48 8b 11 mov (%rcx),%rdx 400c33: 48 8b 42 48 mov 0x48(%rdx),%rax 400c37: 48 89 41 10 mov %rax,0x10(%rcx) 400c3b: 48 89 4a 48 mov %rcx,0x48(%rdx) 400c3f: 48 8b 51 08 mov 0x8(%rcx),%rdx 400c43: 48 8b 42 50 mov 0x50(%rdx),%rax 400c47: 48 89 41 18 mov %rax,0x18(%rcx) 400c4b: 48 89 4a 50 mov %rcx,0x50(%rdx) 400c4f: 48 83 c1 40 add $0x40,%rcx

10

[SPEC CPU2000, 181.mcf, gcc 4.2, high optimisation]





400c30: 48 8b 11 mov (%rcx),%rdx 400c33: 48 8b 42 48 mov 0x48(%rdx),%rax 400c37: 48 89 41 10 mov %rax,0x10(%rcx) 400c3b: 48 89 4a 48 mov %rcx,0x48(%rdx) 400c3f: 48 8b 51 08 mov 0x8(%rcx),%rdx 400c43: 48 8b 42 50 mov 0x50(%rdx),%rax 400c47: 48 89 41 18 mov %rax,0x18(%rcx) 400c4b: 48 89 4a 50 mov %rcx,0x50(%rdx) 400c4f: 48 83 c1 40 add $0x40,%rcx

10

[SPEC CPU2000, 181.mcf, gcc 4.2, high optimisation]

... such workloads can be memory-bound





11





11

0.8 1.5 2 2.70.6

0.7

0.8

0.9

1.0

1.1

Normalised CPU cycles for 164.gzip and 181.mcf

Nor

mal

ised

TS

C

Frequency (GHz)

164.gzip (cpu-bound) 181.mcf (memory-bound)





12





12

0.8 1.5 2.0 2.71.0

1.5

2.0

2.5

3.0

3.5

Runtime of 164.gzip (cpu-bound) vs. 181.mcf (memory-bound)

Nor

mal

ised

run

time

Frequency(GHz)

Runtime 181.mcf (memory-bound) Runtime 164.gzip (cpu-bound)




Our analysis

3 generations of AMD Opteron CPUsin server-class systems

13




Our analysis

14

Die codename Sledgehammer

Year 2003

Core count 1

Frequency range 0.8 - 2.0GHz

Voltage range 0.9 - 1.5

Process 130nm

TDP 89W

Die area 193mm2

Transistor count 106M




Sledgehammer

15




Sledgehammer

0.75

1.00

1.25

1.50

0.8 1 1.6 1.8 2

Energy and runtime of 181.mcf on Sledgehammer

Nor

mal

ised

ene

rgy/

runt

ime

Frequency (GHz)

Energy Runtime

15




Our analysis

16

Die codename Sledgehammer Santa Rosa

Year 2003 2006

Core count 1 2

Frequency range 0.8 - 2.0GHz 1.0 - 2.4GHz

Voltage range 0.9 - 1.5 0.9 - 1.35V

Process 130nm 90nm

TDP 89W 95W

Die area 193mm2 230mm2

Transistor count 106M 243M




Santa Rosa

17




Santa Rosa

1 1.2 1.4 1.6 1.8 2 2.2 2.40.50

0.75

1.00

1.25

1.50

1.75

Energy and runtime of 181.mcf on Santa Rosa

Nor

mal

ised

ene

rgy/

runt

ime

Frequency (GHz)

Energy 1 instance Runtime 1 instanceEnergy 2 instances Runtime 2 instances

17




Our analysis

18

Die codename Sledgehammer Santa Rosa Shanghai

Year 2003 2006 2009

Core count 1 2 4

Frequency range 0.8 - 2.0GHz 1.0 - 2.4GHz 0.8 - 2.7GHz

Voltage range 0.9 - 1.5 0.9 - 1.35V 1.0 - 1.35V

Process 130nm 90nm 45nm

TDP 89W 95W 75W

Die area 193mm2 230mm2 285mm2

Transistor count 106M 243M 463M




Shanghai

19




Shanghai

0.8 1.5 2 2.71.00

1.44

1.88

2.31

2.75

Energy and runtime of 181.mcf on Shanghai

Nor

mal

ised

ene

rgy/

runt

ime

Frequency (GHz)

Energy 1 instance Runtime 1 instanceEnergy 2 instances Runtime 2 instancesEnergy 4 instances Runtime 4 instances

19




Results

DVFS on Shanghai is ineffective for saving energy!

20




Results

DVFS on Shanghai is ineffective for saving energy!

... but why?

20




Static power

DVFS can only change dynamic power consumptionand static power is increasing!

21




What are the trends?

22





• scaling of transistor technology;

22





• scaling of transistor technology;• increasing memory performance;

22





• scaling of transistor technology;• increasing memory performance;• improved idle/sleep modes; and

22





• scaling of transistor technology;• increasing memory performance;• improved idle/sleep modes; and• multi-core processors.

22




Scaling of transistor technology

In ~7 years:

23





• 130 nm to 45 nm

In ~7 years:

23





• 130 nm to 45 nm • 106 M to 463 M transistors

In ~7 years:

23





• 130 nm to 45 nm • 106 M to 463 M transistors• 193 mm2 to 285 mm2

In ~7 years:

23






• 1 MiB to 8 MiB total SRAM cache

In ~7 years:

23






• 1 MiB to 8 MiB total SRAM cache• Single to quad-core (more later...)

In ~7 years:

23






• 1 MiB to 8 MiB total SRAM cache• Single to quad-core (more later...)

In ~7 years:

Static power is increasing significantly, dynamic power is decreasing

23




Increasing memory performance

In ~7 years:

24





• Much larger CPU SRAM caches (fewer cache-misses)

In ~7 years:

24





• Much larger CPU SRAM caches (fewer cache-misses)• DRAM throughput: 3.2GB/s to 5.33GB/s

In ~7 years:

24





• Much larger CPU SRAM caches (fewer cache-misses)• DRAM throughput: 3.2GB/s to 5.33GB/s • Larger DRAM prefetch distance: 2 to 3 cache-lines

In ~7 years:

24





• Much larger CPU SRAM caches (fewer cache-misses)• DRAM throughput: 3.2GB/s to 5.33GB/s • Larger DRAM prefetch distance: 2 to 3 cache-lines• Dual to triple channel DDR memory-controllers

In ~7 years:

24





• Much larger CPU SRAM caches (fewer cache-misses)• DRAM throughput: 3.2GB/s to 5.33GB/s • Larger DRAM prefetch distance: 2 to 3 cache-lines• Dual to triple channel DDR memory-controllers

In ~7 years:

Fewer pipeline stalls for memory references means code is less memory-bound

24




Improved idle/sleep modes

In ~7 years:

25





In ~7 years:

• From a single ʻhaltʼ mode (ACPI C1)

25





In ~7 years:

• From a single ʻhaltʼ mode (ACPI C1)• To multiple stepped low-power sleep modes (C1 - 4)

25





In ~7 years:

• From a single ʻhaltʼ mode (ACPI C1)• To multiple stepped low-power sleep modes (C1 - 4)

Push towards race-and-halt

25




Multi-core processors

26

Today:





• Single off-chip voltage regulator module (VRM)

26

Today:





• Single off-chip voltage regulator module (VRM)• One or more on-chip PLL clock generator modules

26

Today:





• Single off-chip voltage regulator module (VRM)• One or more on-chip PLL clock generator modules

Per-core DVFS adds complexity to hardware and DVFS algorithms

26

Today:




How much energy can we really save?

27

Up to now, weʼve ignored the performance loss...

We can:





27


• use a different benchmarking methodology;

We can:





27


• use a different benchmarking methodology;• use a different metric;

We can:





27


• use a different benchmarking methodology;• use a different metric;• or both.

We can:




Padding methodology

28




Padding methodology

• Extend shorter executions;

28




Padding methodology

• Extend shorter executions;• Add idle energy

28




Padding methodology


28

0

0.25

0.50

0.75

1.00

Padded vs. non-padded benchmarks

Pow

er c

onsu

mp

tion

Time




Padding methodology


28

0

0.25

0.50

0.75

1.00


Pow

er c

onsu

mp

tion

Static power

Time




Padding methodology


28

0

0.25

0.50

0.75

1.00


Pow

er c

onsu

mp

tion

Low frequency

Static power

Time

tlow




Padding methodology


28

0

0.25

0.50

0.75

1.00


Pow

er c

onsu

mp

tion High frequency

Low frequency

Static power

Time

thigh tlow




Padding methodology


28

0

0.25

0.50

0.75

1.00


Pow

er c

onsu

mp

tion High frequency

Low frequency

Static power

Time

thigh tlow

Idle energy




Padding methodology

29




Padding methodology

29

0.8 1.5 2 2.70.4

0.6

0.8

1.0

Padded energy for 181.mcf on Shanghai

Nor

mal

ised

ene

rgy

Frequency (GHz)

Padded energy 1 Instance Padded energy 2 instances Padded energy 4 instances




Padding methodology

30

What about performance?




Energy-delay product

31




Energy-delay product

31

0.8 1.5 2 2.70.5

1.0

1.5

2.0

2.5

Padded energy-delay product for 181.mcf on Shanghai

Nor

mal

ised

pad

ded

ED

P

Frequency (GHz)

EDP 1 instance EDP 2 instances EDP 4 instances




The future...

32




The future...

32

• 32 nm process already in production;




The future...

32

• 32 nm process already in production;• 22 nm and smaller are on the horizon;




The future...

32

• 32 nm process already in production;• 22 nm and smaller are on the horizon;• caches will get bigger;




The future...

32

• 32 nm process already in production;• 22 nm and smaller are on the horizon;• caches will get bigger;• leakage power will rise;




The future...

32

• 32 nm process already in production;• 22 nm and smaller are on the horizon;• caches will get bigger;• leakage power will rise;• memory performance will continue to improve; and




The future...

32

• 32 nm process already in production;• 22 nm and smaller are on the horizon;• caches will get bigger;• leakage power will rise;• memory performance will continue to improve; and• entry/exit costs to/from sleep modes will improve.




The future...

32

• 32 nm process already in production;• 22 nm and smaller are on the horizon;• caches will get bigger;• leakage power will rise;• memory performance will continue to improve; and• entry/exit costs to/from sleep modes will improve.

What about DVFS?




A glimpse

33




A glimpse

33

1.199 1.333 1.466 1.599 1.733 1.866 1.999 2.133 2.266 2.399 2.533 3.0660.75

1.00

1.25

1.50

1.75

2.00

2.25

Energy, runtime and EDP for Westmere (Core i5-540M)

Nor

mal

ised

ene

rgy,

run

time

and

ED

P

Frequency (GHz)

Runtime Energy Energy-delay product




A glimpse

33

1.199 1.333 1.466 1.599 1.733 1.866 1.999 2.133 2.266 2.399 2.533 3.0660.75

1.00

1.25

1.50

1.75

2.00

2.25

Energy, runtime and EDP for Westmere (Core i5-540M)

Nor

mal

ised

ene

rgy,

run

time

and

ED

P

Frequency (GHz)

Runtime Energy Energy-delay product

Turbo Boost




Concluding remarks

34




Concluding remarks

34

• Transistor scaling is causing higher proportions of static leakage power;




Concluding remarks

34


• smaller core voltages mean DVFS has less range to play with;




Concluding remarks

34



• improving memory performance means fewer opportunities to reduce CPU frequency without significant loss of performance;




Concluding remarks

34




• sleep/idle modes are becoming much more efficient;




Concluding remarks

34




• sleep/idle modes are becoming much more efficient;• DVFS implementations on multi-core processors are

more complex and the cost-benefit is small;




Concluding remarks

34




• sleep/idle modes are becoming much more efficient;• DVFS implementations on multi-core processors are

more complex and the cost-benefit is small;• Optimal energy-efficiency is achieved by running fast.




Future direction

35




Future direction

35

• SIMD workloads




Future direction

35

• SIMD workloads– SSE/3Dnow! workloads require many 64bit operands, which

could increase memory-boundedness




Future direction

35



• Periodic workloads




Future direction

35



• Periodic workloads– MPEG video/audio playback, analyse race-to-halt




Future direction

35



• Periodic workloads– MPEG video/audio playback, analyse race-to-halt– usefulness of sleep modes




Future direction

35




• Analyse and compare the trends for embedded devices




Future direction

35




• Analyse and compare the trends for embedded devices– Mobile phones and netbooks




Intel Atom N270

37




Intel Atom N270

37

0.8 1.067 1.333 1.60.8

1.0

1.2

1.4

1.6

1.8

Energy, runtime and EDP for Atom N270

Nor

mal

ised

ene

rgy,

run

timea

nd E

DP

Frequency (GHz)

Runtime Energy EDP




Intel Core 2 Duo (Ultra-low Voltage)

38

0.8

1.0

1.2

1.4

1.6

1.8

2.0

0.8 1.2 1.4 1.6

Energy, runtime and EDP for MacBook Air (Core2 Duo, ULV)

Nor

mal

ised

ene

rgy,

run

timea

nd E

DP

Frequency (GHz)

Runtime Energy EDP



From imagination to impact

From imagination to impact

dynamic voltage and frequency scaling · etienne le sueur and gernot heiser dynamic voltage and...

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