Green Computing Metrics: Power, Temperature, CO2, … Computing system: Many-cores, Clusters, Grids and Clouds Algorithm and model: task scheduling, CFD.

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Presentation transcript:

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 Compute node Compute node vm Compute node vm File server File server Head node Head node vm job Start a vm Execute job in a vm

Schedule virtual machines PE Scheduling algorithm 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 voltages 3.put VMs to PEs 4.If cannot accommodate, level up PE voltages 5.Level down PE voltages whenever it is possible to accommodate VMs

Simulation Results

Experimental Results

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

Y Z X Rack Hot air Rack Node (x,y,z ) Node (x,y,z ) Data center model (1)

Data center model (2)

Thermal aware scheduling framework

Thermal aware scheduling algorithm (TASA) 1.Get thermal field of data center 2.Get compute node temperature 3.Put hottest job to coldest resources 4.Predict the compute node temperature after job execution 5.If a compute node temperature > redline, set it idle 6.thermal aware backfilling when it is possible

Simulation Real workload logged in Buffalo Univ. Temperature logged FCFS in 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 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 aware resource management Workload model

Command Line Information Task Submission Cyberaide Shell Authentication and Authority Java CoG Kit Secure Web Service Cyberaide Portal Python Client Client Layer Middleware Layer Resource Layer Workflow Information collector Information collector Data Center Cyberaide Green: Software achitecture Thermal-Aware Meta Scheduler