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Evaluating Energy and Performance for Server-Class Hardware Configurations. Chenguang Liu, Jianzhong Huang, Qiang Cao, Shenggang Wan, Changsheng Xie School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China. Challenge Problems.
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Evaluating Energy and Performance for Server-Class Hardware Configurations Chenguang Liu, Jianzhong Huang, Qiang Cao, Shenggang Wan, Changsheng Xie School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China
Challenge Problems • Data Centers 15-40x the energy intensity of typical office buildings • A single rack of servers can be 20 kW • $17k per year (at $.10/kWh) per rack • Hundreds of racks per center • For high-end data centers, energy cost increased as much as 25% annually, and making it a big consideration in the total cost of ownership. chgliu2009@gmail.com
Problem Example • Strategies (software & hardware) —migrate workloads & shut down —become more energy proportional • All of them need qualitative and quantitative reference chgliu2009@gmail.com
Add apples or hamburgers?How much to add? chgliu2009@gmail.com
Energy & Performance Metrics • Energy —the average power(Watts) • Performance —I/O operations per second(IOPS) • Integrated factor —I/O operations per joule chgliu2009@gmail.com
Energy & Performance Info Gather • Energy —ZH101 • Performance —FileBench chgliu2009@gmail.com
Workload Categories cont. • FileServer —a file system workload similar to SPECsfs • Varmail —a /var/mail NFS mail server emulation • WebServer —a mix of open/read/close ops of multiple files in a directory tree • OLTP —a database emulator using I/O model from Oracle 9i chgliu2009@gmail.com
Workload Properties chgliu2009@gmail.com
Test Bed chgliu2009@gmail.com
Elements of Total Energy Consumption —Woverhead =energy for maintaining the server's fundamental operating mode —WCPU, Wmem & Wdisk =energy for workloads on different hardware parts respectively —α, β & γ=the weight factor chgliu2009@gmail.com
Average Power in 6 configurations chgliu2009@gmail.com
When a server does not perform any work, it consumes the most energy. • The workload selection alone cannot reduce idle power, but combined with right-sizing techniques, it can improve power efficiency by prolonging idle periods. • Different workloads exercise the system’s resources differently, directly affecting the additional power chgliu2009@gmail.com
Results in FileServer Workload chgliu2009@gmail.com
Results in Fileserver Workload(cont.) • Performance of fileserver workload is both CPU and memory-critical • The configuration of 1u8g proved to be the most power-efficient one, achieving the top point of 26.7373(iops/J) • Energy of fileserver workload is memory-critical chgliu2009@gmail.com
Results in Varmail Workload chgliu2009@gmail.com
Results in Varmail Workload(cont.) • Performance of Varmail workload is CPU-critical • The configuration of 2u4g proved to be the most power-efficient one, achieving the top point of 15.0094(iops/J) • Energy of Varmail workload is also CPU-critical chgliu2009@gmail.com
Results in WebServer Workload chgliu2009@gmail.com
Results in Webserver Workload(cont.) • Performance of webserver workload is neither CPU nor memory-critical • The configuration of 1u4g(the least power consumption) proved to be the most power-efficient one • Web server’s demand for hardware is easy to meet chgliu2009@gmail.com
Results in OLTP Workload chgliu2009@gmail.com
Results in OLTP Workload(cont.) • Performance of database server workload is neither CPU nor memory-critical • Like web server, 1u4g will be a good choice chgliu2009@gmail.com
In fact and intuitively, as to the characteristic of OLTP processing, α, β and γ should be great values A reasonable explanation may come from the inner mechanism(database lock) of OLTP applications blocking the contributions of hardware enhancement. chgliu2009@gmail.com
Conclusion • Strengthening every aspect of a server configuration is not always a wise thing(not just the matter of hardware configuration) • Since the computing and storage requirements of web server applications are easy to meet and we can't easily improve the performance of OLTP applications, we can aggregate different workloads on the single server according to the actual situation chgliu2009@gmail.com
Conclusion (cont.) • Even in single machine different workloads need different hardware configurations to achieve performance- and energy- efficiency • In the management of a modern datacenter, a hardware configuration adaptor would play a very significant role chgliu2009@gmail.com
THANK YOU Questions? chgliu2009@gmail.com