Power-Efficient Server Utilization in Compute Clouds
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- Bernt Lange
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1 Power-Efficient Server Utilization in Compute Clouds 1/14
2 Overview 1. Motivation 2. SPECpower benchmark 3. Load distribution strategies 4. Cloud configuration 5. Results 6. Conclusion 2/14
3 1. Motivation Huge power consumption of data centers Often underutilizied resources Smart load distribution (of the virtual machines) should minimize the total power consumption 3/14
4 2. SPECpower Benchmark Fakultät für Mathematik und Informatik Server Side Java (SSJ): SPECpower_ssj2008 Java Apps with discrete load levels (0,10%,, 100%) Measured power consumption of commonly used servers SPEC Standard Performance Evaluation Corporation 4/14
5 SPEC data for a server Fakultät für Mathematik und Informatik 5/14
6 3. Load distribution strategies Fakultät für Mathematik und Informatik Four strategies for divisible loads: 1. Relative load balancing 2. Absolute load balancing 3. Best performance to power first 4. Adaptive load distribution 6/14
7 Relative load balancing Fakultät für Mathematik und Informatik Compute the percentage of requested load to total maximum performance Assign to each server 7/14
8 Absolute load balancing (alb) Assigns the same amount o/n to each server Fakultät für Mathematik und Informatik If : excess load of server i will be equally distributed to more powerful servers 8/14
9 Best performance to power first (bppf) Sort servers regarding their performance to power ratio (100% load) in decreasing order Assign to each server its is completely distributed until the requested load o Remaining servers will be idle 9/14
10 Adaptive Load Distribution (ald) Find best scaling for each server by minimizing Constrains 10/14
11 4. Cloud configuration Fakultät für Mathematik und Informatik Heterogeneous Server-Hardware Nov Okt Single Server (mainly Intel Xeon-based) 4 Cluster System (1x4,1x16,1x18,1x32) SPEC Performance/Power values: Power consumption: 5,3 19,1 kw 11/14
12 5. Results 12/14
13 Energy consumption for one day time -15% saving to alb If best solution for each load used 13/14
14 6. Conclusion Assuming divisible loads in cloud environments described by SPECpower data Four different load distribution strategies Most sophisticated one is close to the best solution improves power-efficiency just by approx. 9% Power consumption of idle nodes Load-controlled switching of the servers could help to further improve power-efficiency 14/14
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