parrobaartecsecs_11-03-13

“Ingeniamos el futuro”

CAMPUS OF

INTERNATIONAL

EXCELLENCE

DVFS STUDY IN DATA CENTER INFRASTRUCTURES

ENERGY EFFICIENCY APPLICATION

Patricia Arroba García


CAMPUS OF

INTERNATIONAL

EXCELLENCE

Contents

1. Research objective

2. Context

3. Motivation

4. Energy model

5. Energy profiling

6. Results

7. Conclusions

8. Future work

2 Patricia Arroba | DVFS study in Data Center infrastructures


CAMPUS OF

INTERNATIONAL

EXCELLENCE

Research objective

• Reducing energy consumption in Cloud computing data centers

– Application awareness

– Thermal behavior awareness

• Management of low power modes (DVFS)

• Resource selection and consolidation

• Task scheduling



CAMPUS OF

INTERNATIONAL

EXCELLENCE

Research objective

• DVFS in general purpose computing represents savings about 70%

• Energy consumption in Data Centers is dominated by consumption of idle hosts

• In practice, Data Centers do not use DVFS



CAMPUS OF

INTERNATIONAL

EXCELLENCE

Context

• State of the art: DVFS policies *

– frequency Dynamic energy consumption

• Consequence

task execution Static Energy consumption

5

Patricia Arroba | DVFS study in Data Center infrastructures

*E. Quintana: Considers this consequence in his research “Energy-Aware Matrix Computations on Multi-Core and Many-core Platforms”

time


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INTERNATIONAL

EXCELLENCE

Context

• State of the art: Energy consumption models

– Dynamic energy = f ( f, V, CPU load %)

– Static energy = f ( T or T3) fitting complexity

• Consequence

– Weak static energy consumption model

frequency and voltage dependencies missing

simplified temperature dependance

6



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INTERNATIONAL

EXCELLENCE

Motivation

Practical evaluation in real servers

• Validation of a complete energy model

• Analyzing the impact of:

– CPU load %

– Temperature

– DVFS modes & execution time

on the overall energy consumption

7



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INTERNATIONAL

EXCELLENCE

Energy model

8

(Taylor Series)


m: host i: task k: DVFS mode


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Energy model

9

Leakage energy of the rest of the server (NOT CPU) It does not depend on the DVFS mode. Fixed frequency.



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INTERNATIONAL

EXCELLENCE

Energy model



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INTERNATIONAL

EXCELLENCE

Energy Profiling

• Server: Intel Xeon RX300 – 1 CPU, 8 threads hardware

– 7 DVFS modes 1.73 – 2.4 GHz

– Tools: Ipmitool (PTOT, TCPU), perf (IPC), ps(CPU%)

cpufrequtils (DVFS modes)

• Workload: Lookbusy – Synthetic workload

– Highly controllable (CPU load %)

– Does not affect other devices (memory, disk, ... )



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INTERNATIONAL

EXCELLENCE

Curve fitting

• Matlab fitting functions

– Maximum fitting error = 13.61 %

– Mean fitting error = 2.02 %



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INTERNATIONAL

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Model application results:

Dynamic Energy vs load CPU%


Wh

%


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EXCELLENCE


Leakage vs load CPU


Wh

Hz


CAMPUS OF

INTERNATIONAL

EXCELLENCE

15


Leakage vs temperature


Wh

Hz


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INTERNATIONAL

EXCELLENCE

• Temp: 303 K

16


Energy vs DVFS (CPU 10%)

• Temp: 315 K

Difference (Temp.) 5%

Difference (DVFS) 12% Difference (DVFS) 13%


Wh Wh

Hz Hz


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INTERNATIONAL

EXCELLENCE

17


Energy vs DVFS (CPU 100%)

• Temp: 303 K • Temp: 315 K

Difference (Temp.) 5%

Difference (DVFS) 5.5% Difference (DVFS) 6.8%


Wh Wh

Hz Hz


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INTERNATIONAL

EXCELLENCE

Conclusions


Energy-Aware Matrix Computations on Multi-Core and Many-core Platforms. E. Quintana


CAMPUS OF

INTERNATIONAL

EXCELLENCE

Conclusions

• Energy model validated in a real server

• The state of the art does not take into account

the execution time penalty in the static energy

consumption

– Consumption only activating CPU: Best savings for the highest operating frequency

• Promising future work



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INTERNATIONAL

EXCELLENCE

Future work

• Static energy consumption masks CPU dynamic consumption so the static contribution dominates the DVFS policy

• Memory consumption is significant as its contribution will increase the percentage of dynamic consumption



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INTERNATIONAL

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Future work

• Due to this reason, an optimum DVFS mode could be found to increase energy savings

21

Fixed Optimum


Application features

CPU % Memory demand %

DVFS optimum

Wh

Hz


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INTERNATIONAL

EXCELLENCE

Future work

• Real applications can be characterized by its CPU and memory demand

• DVFS modes can be adjusted to these features to increase the overall data center energy efficiency considering the application

• We have developed a MILP to simulate the allocation of tasks, the resource selection and configuration in a data center infrastructure that will be revised to reflect this new target



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INTERNATIONAL

EXCELLENCE

Publications

• Breaking the Energy-Wall in e-Health Scenarios with a Novel Computing Paradigm. M. Zapater, P. Arroba, J.L. Ayala, J.M. Moya, K. Olcoz, C.A. López-Barrio, FGCS 2013.



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INTERNATIONAL

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Thanks for your attention



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INTERNATIONAL

EXCELLENCE


parrobaartecsecs_11-03-13

Technology