An approach of our Power-Aware Computing

Yoshihiko Hotta†(Advisor) Mitsuhisa Sato††：University of Tsukuba

Power Aware computing

Recently, there has been tremendous interest in poweraware computing even in high performance computing such as
PC cluster– to achieve high density packaging– to reduce managing cost.
– It causes a serious problem even on servers in data center.

Achieving Power-Aware Computing, we have investigated both
software and hardware approach.
– Hardware
Characterization of processor’s power consumption
 Developing and Evaluation low power cluster MegaProto– Software
Profile-based DVFS optimization
 Slack time reclamation
 OpenMP on CMP

11/9/2007

PxP meeting on Feb, 282

Problems of short term DVFS prediction
DVFS facility becomes available in several highperformance processors used in a PC cluster– According to our previous research, the runtime DVFS control
using short-time prediction by OS or firmware may fail to selectthe best gear for some applications in high performance computing
fields.
Knowledge of application beahvior is needed tocontrol the gear for power-perfrmance optimization

Comp.
Comm.
Too short comp.(8ms)cannot make DVS ↑11/9/2007≈ 510 ms
≈ 18 ms
PxP meeting on Feb, 283

Profile-based power-performance
optimization AlgorithmWe propose a profile-based power performance
optimization by using DVS in HPC cluster.

– Exploiting application knowledge by using the execution andpower profile

Overview of our algorithm– Define regions at appropriate locations in user-level sourcecode– Measure actual power consumption and obtain execution
profile for each regions– Choose the best gear for the executions on each region bytaking the DVS overhead for frequency transition intoaccountR1

F1=1.4GHz

R2

F2=1.0GHz

R3

F3=1.0GHzF1=1.4GHz

R2

F2=1.0GHz

Not change gear

DVFS slotting overhead
11/9/2007

R1TimePxP meeting on Feb, 284

The flow of Profile-based DVS optimization① Trial runs for generating
profile Define region
 Obtain profile Execution profile Power profile② Calculate EDP and PDP onprofile All regions @ all gear

③ Select the best gear
 Using our propose algorithm
to take the overhead of DVS
into account④ Applying the results inactual run
11/9/2007

PxP meeting on Feb, 285

PowerWatch : A Power Profile System

We have designed and developed the power profiling system.
set_powernow_mode()
set_longrun_status()

Power-monitoringsystem

DVFS library

Cluster

Measurement startwePor

Networki leofPr

Real time GUInggyilplinpuaedhscExecution

Hall Device

Tlog Tool

profileOptimization Algorithm

Execution profile

Power Watch : A Power Profile System
11/9/2007

PxP meeting on Feb, 286

Result of Turion cluster
PDP-aware EDP-aware standard frequency

1.4

re la tiv e ra tio

1.2
10.8
0.6
0.4

All benchmarks can reduce PDP(more than 20%, in some case)

0.2

EDP-aware optimization can reduce
EDP (more than 20% in some case)

0PDP

EDP
ISPerf.

PDP

EDP

Perf.

PDP

CG

EDP

Perf.

PDP

FT

EDP

Perf.

MG

Fig : The result of two types of optimization normalized to standard frequency

11/9/2007

PxP meeting on Feb, 287

Conclusion
We have proposed a profile-based power
performance optimization algorithm by using DVS
in a HPC cluster.

– Our algorithm takes into account the overhead of DVS
transition for avoiding wasted transition.
– We have designed PowerWatch for obtaining actual powerand execution profile.
– We have examined the effect of our algorithm on two typesof low power cluster. The result shows that it reduce theEDP more than 30%.

For future work

– Automatic instrumentation to define more effective regions.
– Adaptation of our algorithm to large scale systems byestimating power profile from the small system’s results.

11/9/2007

PxP meeting on Feb, 288