• Corpus ID: 9286449

Full-System Power Analysis and Modeling for Server Environments

@inproceedings{Economou2006FullSystemPA,
  title={Full-System Power Analysis and Modeling for Server Environments},
  author={Dimitris Economou and Suzanne Rivoire and Christos Kozyrakis and Parthasarathy Ranganathan},
  year={2006}
}
The increasing costs of power delivery and cooling, as well as the trend toward higher-density computer systems, have created a growing demand for better power management in server environments. Despite the increasing interest in this issue, little work has been done in quantitatively understanding power consumption trends and developing simple yet accurate models to predict full-system power. We study the component-level power breakdown and variation, as well as temporal workload-specific… 
csl.stanford.edu
374 Citations
Highly Influential Citations
21
Background Citations
127
Methods Citations
117
Results Citations
9

Figures from this paper

374 Citations

Citation Type

Citation Type

Modeling System-Level Power Consumption Profiles Using RAPL
TLDR
This work presents a prototype lightweight software-based virtual power meter that offers comparable or superior performance to existing power models that are more complex and is viable for use in real-world applications such as power estimation for energy-aware scheduling.
A Comparison of High-Level Full-System Power Models
TLDR
This analysis shows that a model based on OS utilization metrics and CPU performance counters is generally most accurate across the machines and workloads tested, and is particularly useful for machines whose dynamic power consumption is not dominated by the CPU, as well as machines with aggressively power-managed CPUs.
A review of power consumption models of servers in data centers
Measurement, Modeling, and Characterization for Power-Aware Computing
TLDR
This thesis presents techniques to measure power consumption of computer systems at various levels, and performs a detailed performance and energy characterization of Intel’s Restricted Transactional Memory (RTM).
Measuring and rating the energy-efficiency of servers
Dynamic energy allocation for coordinated optimization in enterprise workloads
TLDR
An adaptive infrastructure is discussed to synthesize models that dynamically estimate the throughput and latency characteristics based on component level power distribution in a server to demonstrate modeling accuracy and improvement in energy efficiency due to coordinated power allocation among server components.
Run-Time Prediction of Power Consumption for Component Deployments
TLDR
This paper introduces a model to predict the power consumption of component placements at run-time based on the load and power profile collected for a running distributed application in a heterogeneous environment, and presents a model that enables the use of the approach without dedicated power measurement devices.
Joulemeter: Virtual Machine Power Measurement and Management
TLDR
The results show that not only the savings that were earlier achieved using physical server power capping can be reclaimed on virtualized platforms, but further savings in provisioning costs are enabled due to virtualization.
A Simple Model for Estimating Power Consumption of a Multicore Server System
TLDR
This paper proposes a simple power model for a multicore server that is simple enough to gather only four parameters: operating frequency, the number of active cores, theNumber of cache accesses and thenumber of the last level cache misses.
Performance Events Based Full System Estimation on Application Power Consumption
  • Shu Yang, Zhongzhi Luan, Binyang Li, Ge Zhang, Tianming Huang, D. Qian
  • Computer Science, Engineering
    2016 IEEE 18th International Conference on High Performance Computing and Communications; IEEE 14th International Conference on Smart City; IEEE 2nd International Conference on Data Science and Systems (HPCC/SmartCity/DSS)
  • 2016
TLDR
The power models proposed in this paper can provide software developers or system designers with visible power behaviors for the applications and can make decisions or change code to develop more energy-efficient software.
...
...

References

SHOWING 1-10 OF 40 REFERENCES
A performance-conserving approach for reducing peak power consumption in server systems
TLDR
The solution, Power Shifting, reduces the peak power consumption of servers minimizing the impact on performance by using workload-guided dynamic allocation of power among components incorporating real-time performance feedback, activity-related power estimation techniques, and performance-sensitive activity-regulation mechanisms to enforce power budgets.
Using complete machine simulation for software power estimation: the SoftWatt approach
TLDR
A complete system power simulator, called SoftWatt, is presented that models the CPU, memory hierarchy, and a low-power disk subsystem and quantifies the power behavior of both the application and operating system.
Design and validation of a performance and power simulator for PowerPC systems
TLDR
The design and validation of a performance and power simulator that is part of the Mambo simulation environment for PowerPC® systems, designated as Tempo, and examples of how well it can predict the runtime power consumption of a 405GP microprocessor during application execution are shown.
Power prediction for Intel XScale processors using performance monitoring unit events
TLDR
A first-order, linear power estimation model that uses performance counters to estimate run-time CPU and memory power consumption of the Intel PXA255 processor that can serve as a foundation for intelligent, poweraware embedded systems that dynamically adapt to the device’s power consumption is demonstrated.
Power prediction for Intel XScale/spl reg/ processors using performance monitoring unit events
  • Gilberto Contreras, M. Martonosi
  • Computer Science
    ISLPED '05. Proceedings of the 2005 International Symposium on Low Power Electronics and Design, 2005.
  • 2005
TLDR
A first-order, linear power estimation model that uses performance counters to estimate run-time CPU and memory power consumption of the Intel PXA255 processor that can serve as a foundation for intelligent, power-aware embedded systems that dynamically adapt to the device's power consumption is demonstrated.
Run-time power estimation in high performance microprocessors
TLDR
The Castle project is presented, which aims to deduce the actual runtime power dissipated by different processor units on the CPU chip by leveraging existing hardware.
Wattch: a framework for architectural-level power analysis and optimizations
TLDR
Wattch is presented, a framework for analyzing and optimizing microprocessor power dissipation at the architecture-level and opens up the field of power-efficient computing to a wider range of researchers by providing a power evaluation methodology within the portable and familiar SimpleScalar framework.
Modeling Hard-Disk Power Consumption
TLDR
Dempsey, a disk simulation environment that includes accurate modeling of disk power consumption, is presented, which includes tools to automatically extract performance and power consumption parameters from a given disk drive, without needing detailed specifications from the manufacturer.
Process cruise control: event-driven clock scaling for dynamic power management
TLDR
An energy-aware scheduling policy for non-real-time operating systems that benefits from event counters is proposed and energy measurements of the target architecture under variable load show the advantage of the proposed approach.
MEMPOWER: A Simple Memory Power Analysis Tool Set
TLDR
This report describes the theory, structure and implementation characteristics of MEMPOWER and provides a sample evaluation of memory power and energy under various policies based on a memory trace taken with the Mambo full-system simulator.
...
...