TRACER: A Trace Replay Tool to Evaluate Energy-Efficiency of Mass Storage Systems

1. TRACER: A Trace Replay Tool to Evaluate Energy-Efficiency of Mass Storage Systems Zhuo Liu, Fei Wu , Xiao Qin,Changsheng Xie, Jian Zhou, and Jianzong Wang WNLO, Huazhong University of Science and Technology; Computer Science Department, Auburn University liuzhuo9090@gmail.com

2. Outline I. Motivation Why do we need TRACER? II. Architecture What does TRACER consist of? How does TRACER work and look like? III. Trace-replay control scheme How does TRACER control load intensity? IV. Measurement How well does TRACER work? V. Conclusion and future work

3. I Motivation • New energy conservation techniques in storage systems constantly spring up: • such as MAID, DRPM, PDC… • Lack of systematic and uniform way to evaluate them: • present benchmarks and standards are most forCPU-intensive applications

4. Current power-aware techniques

5. Energy-efficiency Standards • SPEC (CPU-intensive) • Metric: Java_ops/Watt • SUN swap (CPU-intensive) • Metric: Performance/(Space*Watt) • Joule Sort (CPU-intensive) • Metric: Sort_ops/Joule • Energy Star • SNIA green • Classification of storage devices • Standards mainly for idle-mode tests

6. Power increases with load intensity SNIA-Green

7. What should TRACER do? TRACER Test the power consumptions Produce different modes of IO load Regulate IO load intensity: 10%-100% Metrics: to evaluate energy-efficiency

8. II. Architecture of TRACER • TRACER consists of four parts: • Evaluation host • Workload generator • Power analyzer • Storage systems under test

9. What does TRACER consist of?

10. How is TRACER implemented?

11. GUI of TRACER

12. III. Trace-replay control scheme The structure of a blocktrace file

13. Load-control algorithm for trace replay

14. IV. Measurement: environment

15. Measurement: hardware connects

16. Measurement : traces Three types of traces: 125 traces we connected using IOmeter Request size: 512B, 4KB, 16KB, 64KB, 1MB Random/sequential%: 0% ,25%, 50%, 75%,100% Read/write%: 0%, 25% ,50% ,75%, 100% HP lab: cello 96 and cello 99 The web server trace (FAST’09-BORG)

17. Measurement : evaluation metrics IO Throughput/Power Consumption IOPS/Watt MBPS/Kilowatt

18. V. Measurement: results • 1. Accuracy of load control for 125 traces • Accuracy % =Measured intensity% / configured% • 2. How Energy-efficiency is influenced • By load intensity • By random% • By read% • 3. Accuracy for Real traces • HP lab cello99 cello96, web server traces

19. Accuracy of load control

20. E-E influenced by load%

21. E-E influenced by random%

22. E-E influenced by read%

23. Load control for real trace

24. Accuracy of load control for real trace

25. Conclusion and Future Work 1 TRACER is accurate, efficient and useful. 2 Storage system is more energy-efficient under higher load intensity, under lower random rate. 3 As temperature influences system’s performance and power, it’s necessary to add temperature as part of evaluation metrics.

26. Add Temperature metrics Temp sensor

27. Thank You ! Any question? liuzhuo9090@gmail.com