Green Computing

• Metrics: Power, Temperature, CO2, …• Computing system: Many-cores, Clusters,

Grids and Clouds• Algorithm and model: task scheduling, CFD

model, …• Middleware: auditing & insertion service,

green resource management service, …

Power aware virtual machine scheduling in a DVFS cluster

• Virtual machine in Grids and Clouds• Dynamic Voltage Frequency Scheduling • Objective: dynamically scale voltages for

virtual machines in a cluster

Virtual machines in compute cluster

vm vm

Computenode

vm

Compute node

vmFile

serverHeadnode

vmvm

job

Start a vm

Execute job in a vm

Schedule virtual machines

PE

PE

PE

PE

PE

PE

Scheduling

algorithm

VM

cluster

queue

Power aware scheduling algorithm

1. Sort VMs in a decreasing order of required CPU speed

2. Set PEs to lowest voltages3. put VMs to PEs4. If cannot accommodate, level up PE voltages5. Level down PE voltages whenever it is

possible to accommodate VMs

Simulation Results

36%

2%5%23%

34%

_x0010_0.6 GHz, 0.956 V_x0010_0.8 GHz, 1.180 V_x0010_1.0 GHz, 1.308 V_x0010_1.2 GHz, 1.436 V_x0010_1.4 GHz, 1.484 V

10 20 30 40 500%

20%

40%

60%

80%

100%

vm=100vm=200vm=300vm=400vm=500

PE Number

Nor

mal

ized

Pow

er C

onsu

mpti

on

Experimental Results

2 4 80

10

20

30

40

50

60

70

80

90

100

1.6 GHz1.867 GHz2.133 GHz2.533 GHz2.668 GHz

Number of VMs

nBen

ch In

tege

r Ind

ex

2 4 80

50

100

150

200

250

1.6 GHz1.867 GHz2.133 GHz2.533 GHz2.688 GHz

Number of VMs

Pow

er C

onsu

mpti

on (W

atts)

Thermal aware workload scheduling in data centers

• Job-temperature model• Data center resource model• Thermal aware scheduling algorithm (TASA)• Thermal aware workload scheduling

framework• Simulation

Job-temperature profile

YZ

X

Rack

Hot

air

Hot

air

Rack RackNode(x,y,z)

Data center model (1)

Data center model (2)

Task-temperature profile

Online task-temperature

calculation

RC-thermal model

Workload model

Thermal map

Datacenter model

Thermal aware workload scheduling

algorithm

Profiling tool

Monitoring service

Cooling system control

CFD model

Workload placement

Thermal aware scheduling framework

Thermal aware scheduling algorithm (TASA)

1. Get thermal field of data center2. Get compute node temperature 3. Put hottest job to coldest resources4. Predict the compute node temperature after

job execution5. If a compute node temperature > redline, set

it idle6. thermal aware backfilling when it is possible

Simulation

• Real workload logged in CCR @ Buffalo Univ.• Temperature logged • FCFS in CCR @ Buffalo Univ.• TASA• Discussion

Workload in CCR

CCR Temperature

Simulation Result (1)

• Reduce max temperature: 6 F• Reduce average temperature: 15 F• Reduce power consumption 4000 kW/h• Reduce CO2 emission 19 000 kg

Simulation Result (2)

• Response time increase 13%

Green Data Center Computing: concept

Software sensor

Auditing & Insertion service

Physical sensor

Monitoring service

CFD model

Auditing & Insertion service

Cooling system and compute resources in a data center

Thermal aw

are resource m

anagement

Workload m

odel

Command Line

InformationTask Submission

Cyberaide Shell

Authentication and Authority

Java CoG Kit

Secure Web Service

Secure Web Service

Cyberaide Portal Python Client Client Layer

MiddlewareLayer

Resource Layer

Workflow Informationcollector

Data Center Data Center

Cyberaide Green: Software achitecture

Thermal-Aware Meta Scheduler