Inter-program optimizations for conserving disk energy

Hom, Jerry; Kremer, Ulrich

doi:10.1145/1077603.1077684

Cited by 9 publications

(6 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Later work applied similar techniques to the data center as power became a critical issue for large commercial server farms [18,10,1,3]. Poweraware high-performance computing attempted to develop new techniques that save power and energy without impacting performance in parallel, non-interactive scientific applications.…”

Section: Related Workmentioning

confidence: 99%

CPU MISER: A Performance-Directed, Run-Time System for Power-Aware Clusters

Feng

et al. 2007

2007 International Conference on Parallel Processing (ICPP 2007)

172

127

View full text Add to dashboard Cite

Section: Related Workmentioning

confidence: 99%

CPU MISER: A Performance-Directed, Run-Time System for Power-Aware Clusters

Feng

et al. 2007

2007 International Conference on Parallel Processing (ICPP 2007)

172

127

View full text Add to dashboard Cite

“…Some approaches adapt the compiler to extend, as much as possible, the time between disk accesses to allow switching the disk into a hibernate state, thus saving energy (Hom and Kremer, 2005). The insight into how disk drives use the energy can also provide valuable information related to power consumption (Zedlewski et al, 2003).…”

Section: Power Drawmentioning

confidence: 99%

Profiling Computer Energy Consumption on Organizations

Lopes

Pires

Pedrosa

et al. 2009

Proceedings of the 11th International Conference on Enterprise Information

View full text Add to dashboard Cite

Abstract:Modern organizations depend on computers to work. Text processing, CAD, CAM, simulation, statistical analysis and so on are fundamental for maintaining high degree of productivity and competitiveness. Computers in an organization, consume a considerable percentage of the overall energy and, although a typical computer provides power saving technologies, such as suspending or hibernating components, this feature can be disabled. Moreover, the user can opt for never turning off the workstation. Well defined power saving policies, with appropriate automatic mechanisms to apply them, can provide significant power savings with consequent reduction of the power expense. With several computers in an organization, it is necessary to build the profile of the energy consumption. We propose installing a software probe in each computer to instrument the power comsumption, either diretly, by using a power meter, or indirectly, by measuring the processor performance counters. This distributed architecture, with software probes in every computer and a centralized server for persistence and decision making tries to save energy, by defining and applying organization level power saving policies.

show abstract

“…This optimization works well in uniprogramming environments. However in multiprogramming environments, even just two programs can negate the benefits if their bursty access patterns are unaligned [18]. The interfering disk accesses resembles the original problem of unclustered disk requests in uniprogramming.…”

Section: Related Workmentioning

confidence: 99%

“…They would do better by adapting the hibernation policy threshold [12] or coordinating their accesses. A limited notion of optimizing programs together [18] was introduced to cluster disk requests.…”

Section: Introductionmentioning

confidence: 99%

Execution context optimization for disk energy

Hom

Kremer

2008

Proceedings of the 2008 International Conference on Compilers, Architectures and Synthesis for Embedded Systems

Self Cite

View full text Add to dashboard Cite

Power, energy, and thermal concerns have constrained embedded systems designs. Computing capability and storage density have increased dramatically, enabling the emergence of handheld devices from special to general purpose computing. In many mobile systems, the disk is among the top energy consumers. Many previous optimizations for disk energy have assumed uniprogramming environments. However, many optimizations degrade in multiprogramming because programs are unaware of other programs (execution context). We introduce a framework to make programs aware of and adapt to their runtime execution context.We evaluated real workloads by collecting user activity traces and characterizing the execution contexts. The study confirms that many users run a limited number of programs concurrently. We applied execution context optimizations to eight programs and tested ten combinations. The programs ran concurrently while the disk's power was measured. Our measurement infrastructure allows interactive sessions to be scripted, recorded, and replayed to compare the optimizations' effects against the baseline. Our experiments covered two write cache policies. For write-through, energy savings was in the range 3-63% with an average of 21%. For writeback, energy savings was in the range -33-61% with an average of 8%. In all cases, our optimizations incurred less than 1% performance penalty.

show abstract

Inter-program optimizations for conserving disk energy

Cited by 9 publications

References 10 publications

CPU MISER: A Performance-Directed, Run-Time System for Power-Aware Clusters

CPU MISER: A Performance-Directed, Run-Time System for Power-Aware Clusters

Profiling Computer Energy Consumption on Organizations

Execution context optimization for disk energy

Contact Info

Product

Resources

About