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Thermal Management in Datacenters

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 in Datacenters

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  1. Thermal Management in Datacenters Ayan Banerjee

  2. 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

  3. 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

  4. CFD Models • Flovent 6.1

  5. 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

  6. Observations • 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

  7. Observations • 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

  8. Experiment • 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.

  9. Task Placement Minimizing Maximum Temperature Maximum Inlet Temperature = 24.6016 degrees Total Power = 162525 W

  10. Task Placement Minimizing Total Energy Task 2 Task 1 Total Energy Consumption = 576592 J MaxTin = 26.3093 C 29.0858 C 27.7871 C

  11. 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

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