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Thermal Management in Datacenters. Ayan Banerjee. Thermal Management using task placement. Tasks: Requires a certain number of servers (cores) for a specified amount of time. Each task has certain power consumption on each server of a particular node.

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thermal management using task placement
Thermal Management using task placement
  • Tasks: Requires a certain number of servers (cores) for a specified amount of time.
  • Each task has certain power consumption on each server of a particular node.
  • Assign cores to the tasks based on certain objective.
  • Remember task placement and not task scheduling
goals of this project
Goals of this project
  • Build CFD model of a real Datacenter
  • Perform thermal profiling
  • Test the performance of different task placement algorithms on this model
  • Simulate Cross Interference minimization algorithm for multiple task scenario arriving at different time intervals
  • Test the optimality of the solutions for different objectives
cfd models
CFD Models
  • Flovent 6.1
difficulties faced with flovent
Difficulties faced with Flovent
  • Simplified Heterogeneous datacenter takes 18 hrs to run the base case
  • Cannot set parameters dynamically
  • According to findings HVAC outlet temperature varies with its inlet temperature
  • Cannot simulate that in Flovent so there will be difficulties in simulating algorithms that try to reduce total energy consumption
  • Energy aware task placement algorithms must take into account the behavior of the Cooling System
  • Basis: AC works harder when the Hot isle temperature in the datacenter increases
  • For the objective of minimizing total energy
    • We have to consider the working of the AC in the objective function
    • We have to consider a heterogeneous Datacenter
    • We have to design algorithms that will allow different jobs to work on the same server
  • Took the simplified CFD model of the Datacenter
  • There were 50 chassis. The design was for homogeneous environment.
  • Built a heterogeneous environment with 20 chassis equipped with dual core processor and the rest 30 chassis with quad core.
  • Total number of cores = 1300.
  • Dual core – idle = 1728 W, Busy = 3260 W

Quad core – idle = 2420 W, Busy = 6020 W

  • Two applications T1 and T2
    • T1 required 288 servers for a time period of 3 units starting from unit 0 to unit 3
    • T2 required 672 cores for a time period of 3 units starting form unit 1 to unit 4
  • Find the solution for the cross interference minimization algorithm for the objective of minimizing Maximum Temperature and minimizing total energy.
task placement
Task Placement

Minimizing Maximum Temperature

Maximum Inlet Temperature = 24.6016 degrees

Total Power = 162525 W

task placement1
Task Placement

Minimizing Total Energy

Task 2

Task 1

Total Energy Consumption = 576592 J

MaxTin = 26.3093 C 29.0858 C 27.7871 C

goals revisited
Goals Revisited
  • CFD Model of Datacenter not yet ready
    • We have information on Saguaro Racks but little information on other racks
    • Certain physical parameters need to be recorded
  • Power Profiling not done as a result of incomplete CFD Model
  • Simulation Environment for multiple task arriving at different times ready
  • Optimality of the cross interference minimization algorithm tested
  • Apart form the cited goals a lot of observations useful for future work are made