%0 Conference Paper %1 KiBlBeLaArKo2015-ICPE-SERT %A von Kistowski, Jóakim %A Block, Hansfried %A Beckett, John %A Lange, Klaus-Dieter %A Arnold, Jeremy A. %A Kounev, Samuel %B Proceedings of the 6th ACM/SPEC International Conference on Performance Engineering (ICPE 2015) %C New York, NY, USA %D 2015 %I ACM %K Instrumentation_profiling_and_workload_characterization Metrics_and_benchmarking_methodologies Performance Power Power-energy_efficient_computing SPEC descartes t_full %T Analysis of the Influences on Server Power Consumption and Energy Efficiency for CPU-Intensive Workloads %X Energy efficiency of servers has become a significant research topic over the last years, as server energy consumption varies depending on multiple factors, such as server utilization and workload type. Server energy analysis and estimation must take all relevant factors into account to ensure reliable estimates and conclusions. Thorough system analysis requires benchmarks capable of testing different system resources at different load levels using multiple workload types. Server energy estimation approaches, on the other hand, require knowledge about the interactions of these factors for the creation of accurate power models. Common approaches to energy-aware workload classification classify workloads depending on the resource types used by the different workloads. However, they rarely take into account differences in workloads targeting the same resources. Industrial energy-efficiency benchmarks typically do not evaluate the system's energy consumption at different resource load levels, and they only provide data for system analysis at maximum system load. In this paper, we benchmark multiple server configurations using the CPU worklets included in SPEC's Server Efficiency Rating Tool (SERT). We evaluate the impact of load levels and different CPU workloads on power consumption and energy efficiency. We analyze how functions approximating the measured power consumption differ over multiple server configurations and architectures. We show that workloads targeting the same resource can differ significantly in their power draw and energy efficiency. The power consumption of a given workload type varies depending on utilization, hardware and software configuration. The power consumption of CPU-intensive workloads does not scale uniformly with increased load, nor do hardware or software configuration changes affect it in a uniform manner.

@inproceedings{KiBlBeLaArKo2015-ICPE-SERT, abstract = {{ Energy efficiency of servers has become a significant research topic over the last years, as server energy consumption varies depending on multiple factors, such as server utilization and workload type. Server energy analysis and estimation must take all relevant factors into account to ensure reliable estimates and conclusions. Thorough system analysis requires benchmarks capable of testing different system resources at different load levels using multiple workload types. Server energy estimation approaches, on the other hand, require knowledge about the interactions of these factors for the creation of accurate power models. Common approaches to energy-aware workload classification classify workloads depending on the resource types used by the different workloads. However, they rarely take into account differences in workloads targeting the same resources. Industrial energy-efficiency benchmarks typically do not evaluate the system's energy consumption at different resource load levels, and they only provide data for system analysis at maximum system load. In this paper, we benchmark multiple server configurations using the CPU worklets included in SPEC's Server Efficiency Rating Tool (SERT). We evaluate the impact of load levels and different CPU workloads on power consumption and energy efficiency. We analyze how functions approximating the measured power consumption differ over multiple server configurations and architectures. We show that workloads targeting the same resource can differ significantly in their power draw and energy efficiency. The power consumption of a given workload type varies depending on utilization, hardware and software configuration. The power consumption of CPU-intensive workloads does not scale uniformly with increased load, nor do hardware or software configuration changes affect it in a uniform manner.}}, added-at = {2020-04-05T23:17:34.000+0200}, address = {New York, NY, USA}, author = {von Kistowski, J{\'o}akim and Block, Hansfried and Beckett, John and Lange, Klaus-Dieter and Arnold, Jeremy A. and Kounev, Samuel}, biburl = {https://www.bibsonomy.org/bibtex/2f08de47ded0479ffc20daf46823e1f7e/se-group}, booktitle = {Proceedings of the 6th ACM/SPEC International Conference on Performance Engineering (ICPE 2015)}, interhash = {9a605db81a881cb316d73182870feca0}, intrahash = {f08de47ded0479ffc20daf46823e1f7e}, keywords = {Instrumentation_profiling_and_workload_characterization Metrics_and_benchmarking_methodologies Performance Power Power-energy_efficient_computing SPEC descartes t_full}, month = {February}, note = {acceptance rate: 27\%}, publisher = {ACM}, series = {ICPE '15}, timestamp = {2020-10-06T10:03:33.000+0200}, title = {{Analysis of the Influences on Server Power Consumption and Energy Efficiency for CPU-Intensive Workloads}}, year = 2015 }