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Studying Hardware and Software Trade-Offs for a Real-Life Web 2.0 Workload

Studying Hardware and Software Trade-Offs for a Real-Life Web 2.0 Workload. Authors: Stijn Polfliet et. al. By: Ali Nikravesh. Agenda. Introduction - What is the research question? What is authors’ approach to address the problem? Results. Introduction. Online Social Networking

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Studying Hardware and Software Trade-Offs for a Real-Life Web 2.0 Workload

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  1. Studying Hardware and Software Trade-Offs for a Real-Life Web 2.0 Workload Authors: StijnPolfliet et. al. By: Ali Nikravesh

  2. Agenda • Introduction - What is the research question? • What is authors’ approach to address the problem? • Results

  3. Introduction • Online Social Networking • Facebook • Twitter • LinkedIn • Netlog • Large number of users  designing the servers and data centres to support social networking is challenging • Large scale data centres  very much cost driven

  4. Introduction (contd.) • Factors that affect the cost of data centre: • Hardware infrastructure • Power and cooling infrastructure • Operating expenditure • Real estate • Increase performance increase cost  • Reduce cost   reduce performance  • RESULT  optimize performance per dollar

  5. Introduction (contd.) • So, which server should be bought? • Depends on workload (interactive, batch, memory intensive,…) • Idea: different workloads run on different hardware • Correct hardware for correct task 

  6. Introduction (contd.) • Research Question: • Scope: Social networking Can we come up with a way of guiding service operators and owners of data centre to what hardware to purchase for a given workload?

  7. Analysis • Social networking workload • Multiple services run on multiple servers in a distributed way in a data center • Fundamental difficulty  performance of the ensemble can only be measured by modeling and evaluating the ensemble  • Authors’ approach: A case study to evaluate how hardware choices affect end-user experience

  8. Case study • Netlog • Is a social network available in 40 languages • Architecture • WS 54% • MC 16% • DB 30%

  9. Experimental Setup • 10 dual AMD Opteron 6168 servers • 12 cores per CPU • 64 GB of main memory • HDD & SSD

  10. Web Server Results • Three CPU frequency • 1.9 GHz • 1.3 GHz • 800 Mhz • Frequency has a significant impact on response time.

  11. Web Server Results (contd.) • Number of cores per node • Four-socket system is typically more than twice as expensive as a two-socket system. • As long as the total number of cores is constant, CPU node is not affected much by node and core count

  12. Database Server • Database server: HDD versus SDD • Although this is a significant reduction in the longest response times observed, it may not justify the significantly higher cost of SSD versus HDD

  13. Memcached Server • Average CPU load for memcached server is typically below 5%

  14. Usecase • Hardware Purchasing • Hardware vendor suggestion: • Web server: Intel Xeon X3480, 8 GB RAM, typical HDD ($1795) • Memcached server: Intel Xeon X3480, 16GB RAM, typical HDD ($2015) • Database server: Intel Xeon X3480, 16GB RAM, SSD ($2915) • Total: $18615 • Suggestion • Web server the same as above. Memcached the same as Web server but lower CPU frequency. DB the same as memcached but not SSD (Total: $15015 – 18.9% reduction) • Performance Evaluation: • 50% of all requests will not experience any extra latency • For other 50%, increase from 11% to 39%

  15. Thanks Questions?

  16. Les important diagrams 1 • Comparing simulation response with actual response packets

  17. Les important diagrams 2 • Sampling in time • Traffic classified by its type

  18. Les important diagrams 3 • Warm-up

  19. Les important diagrams 4 • CPU load as a function of clock frequency • CPU load as a func of cores

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