Emulating the Power Consumption Behavior of Server Workloads Using CPU Performance Counters

The accurate measurement of a server's power consumption when running realistic workloads enables characterization of its energy efficiency and helps to make better provisioning and workload placement decisions. Information on the energy efficiency of a server for a given target workload can greatly influence such decisions and thus the final energy efficiency of a cluster or data center. However, measuring energy efficiency and power consumption of server applications has become challenging as applications are often distributed or require work intensive configuration, setup, and specialized load drivers for reproducible testing. As a result, it may be not feasible to perform tests using the actual workload that is to be deployed. We introduce an approach to create small-scale workloads that emulate the power consumption-relevant behavior of an application by deliberately triggering specific power relevant performance counter events. These workloads can then be easily deployed on a target server for fast and efficient power characterization. We validate the proposed approach by approximating the power consumption behavior of different workloads at multiple load levels. We show that our approach is capable of producing small-scale workloads that reflect the power consumption behavior of their reference applications over multiple load levels with a minimum error of less than 1%.

[1]  Klaus-Dieter Lange,et al.  The design and development of the server efficiency rating tool (SERT) , 2011, ICPE '11.

[2]  Sally A. McKee,et al.  Real time power estimation and thread scheduling via performance counters , 2009, CARN.

[3]  Matthias Hauswirth,et al.  Accuracy of performance counter measurements , 2009, 2009 IEEE International Symposium on Performance Analysis of Systems and Software.

[4]  Sheldon Howard Jacobson,et al.  The Theory and Practice of Simulated Annealing , 2003, Handbook of Metaheuristics.

[5]  Vincent M. Weaver.  Self-monitoring overhead of the Linux perf_ event performance counter interface , 2015, 2015 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS).

[6]  Frank Bellosa,et al.  The benefits of event: driven energy accounting in power-sensitive systems , 2000, ACM SIGOPS European Workshop.

[7]  Mahmut T. Kandemir,et al.  vEC: virtual energy counters , 2001, PASTE '01.

[8]  Margaret Martonosi,et al.  Runtime Power Monitoring in High-End Processors: Methodology and Empirical Data , 2003, MICRO.

[9]  Margaret Martonosi,et al.  Power prediction for Intel XScale/spl reg/ processors using performance monitoring unit events , 2005, ISLPED '05. Proceedings of the 2005 International Symposium on Low Power Electronics and Design, 2005..

[10]  Raffaele Bolla,et al.  DROPv2: energy efficiency through network function virtualization , 2014, IEEE Network.

[11]  Michael F. P. O'Boyle,et al.  Rapidly Selecting Good Compiler Optimizations using Performance Counters , 2007, International Symposium on Code Generation and Optimization (CGO'07).

[12]  Samuel Kounev,et al.  Analysis of the Influences on Server Power Consumption and Energy Efficiency for CPU-Intensive Workloads , 2015, ICPE.

[13]  Yonggang Wen,et al.  Energy efficiency and server virtualization in data centers: An empirical investigation , 2012, 2012 Proceedings IEEE INFOCOM Workshops.

[14]  Lizy Kurian John,et al.  Complete System Power Estimation Using Processor Performance Events , 2012, IEEE Transactions on Computers.

[15]  Nian-Feng Tzeng,et al.  Run-time Energy Consumption Estimation Based on Workload in Server Systems , 2008, HotPower.

[16]  Samuel Kounev,et al.  Energy Efficiency of Hierarchical Server Load Distribution Strategies , 2015, 2015 IEEE 23rd International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems.

[17]  Samuel Kounev,et al.  Variations in CPU Power Consumption , 2016, ICPE.

[18]  James E. Smith,et al.  A performance counter architecture for computing accurate CPI components , 2006, ASPLOS XII.

[19]  Shirley Moore,et al.  Non-determinism and overcount on modern hardware performance counter implementations , 2013, 2013 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS).

[20]  Gilberto Contreras,et al.  Power prediction for Intel XScale processors using performance monitoring unit events , 2005 .