Compile-time dynamic voltage scaling settings

Xie, Fangxia; Martonosi, Margaret; Malik, Sharad

doi:10.1145/781131.781138

Cited by 89 publications

(43 citation statements)

References 18 publications

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“…The third example is introduced by Xie, and is closest to our work. Xie's work [32,34,33] uses an ILP model to determine maximum energy savings on a single processor, develops a heuristic that approximates the ILP very well and runs much faster, and proposes an analytic model that allows DVS to be applied across separate programs. Our goals and techniques are similar in that we both use mathematical models to bound the maximum energy savings.…”

Section: Related Workmentioning

confidence: 99%

Bounding energy consumption in large-scale MPI programs

Rountree

Lowenthal

Funk

et al. 2007

Proceedings of the 2007 ACM/IEEE Conference on Supercomputing

128

115

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Power is now a first-order design constraint in large-scale parallel computing. Used carefully, dynamic voltage scaling can execute parts of a program at a slower CPU speed to achieve energy savings with a relatively small (possibly zero) time delay. However, the problem of when to change frequencies in order to optimize energy savings is NP-complete, which has led to many heuristic energysaving algorithms.To determine how closely these algorithms approach optimal savings, we developed a system that determines a bound on the energy savings for an application. Our system uses a linear programming solver that takes as inputs the application communication trace and the cluster power characteristics and then outputs a schedule that realizes this bound. We apply our system to three scientific programs, two of which exhibit load imbalance-particle simulation and UMT2K. Results from our bounding technique show particle simulation is more amenable to energy savings than UMT2K.

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Section: Related Workmentioning

confidence: 99%

Bounding energy consumption in large-scale MPI programs

Rountree

Lowenthal

Funk

et al. 2007

Proceedings of the 2007 ACM/IEEE Conference on Supercomputing

128

115

View full text Add to dashboard Cite

show abstract

“…DVFS is being used in commercial processors across the entire computing range: from the embedded and mobile market up to the server market. Extensive research has been done towards how to take advantage of DVFS and reduce overall energy consumption while meeting specific performance targets, or improving performance while not exceeding a given power budget, either through the operating system [17], managed runtime system [23], compiler [12,24] or architecture [14,16,21].…”

Section: Dvfsmentioning

confidence: 99%

Exploring multi-threaded Java application performance on multicore hardware

Sartor

Eeckhout

2012

Proceedings of the ACM International Conference on Object Oriented Programming Systems Languages and Applications

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While there have been many studies of how to schedule applications to take advantage of increasing numbers of cores in modern-day multicore processors, few have focused on multi-threaded managed language applications which are prevalent from the embedded to the server domain. Managed languages complicate performance studies because they have additional virtual machine threads that collect garbage and dynamically compile, closely interacting with application threads. Further complexity is introduced as modern multicore machines have multiple sockets and dynamic frequency scaling options, broadening opportunities to reduce both power and running time.In this paper, we explore the performance of Java applications, studying how best to map application and virtual machine (JVM) threads to a multicore, multi-socket environment. We explore both the cost of separating JVM threads from application threads, and the opportunity to speed up or slow down the clock frequency of isolated threads. We perform experiments with the multi-threaded DaCapo benchmarks and pseudojbb2005 running on the Jikes Research Virtual Machine, on a dual-socket, 8-core Intel Nehalem machine to reveal several novel, and sometimes counterintuitive, findings. We believe these insights are a first but important step towards understanding and optimizing managed language performance on modern hardware.

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“…Performance engineering will contribute to these efforts building several power models for servers executing web different workloads in extensive studies including regression models and also simulation. Other techniques include multiserver power coordination [43], hard disk spin-down [40], synchronization aware multithreading [42], and compiler driven optimizations [49]. Another interesting issue is server virtualization, where hardware elements are managed by a datacenter-wide software stack that spans the platforms and virtualization layers.…”

Section: State Of the Artmentioning

confidence: 99%

From the Origins of Performance Evaluation to New Green ICT Performance Engineering

Juiz

Puigjaner

2011

Performance Evaluation of Computer and Communication Systems. Milestones and Future Challenges

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Abstract. This paper intends to present an overview of the evolution of performance evaluation since its first steps the Erlang works for modelling telephone networks, based on simple queues until the present current challenges in Green ICT that will require the development of new paradigms and mathematical tools, and rapidly passing across the modelling works of Khintchine and Pollaczeck; Jackson; Baskett, Chandy, Muntz and Palacios; Buzen; Reiser and Lavenberg; and many others, and benchmarking standards that have produced solutions to the problems appearing in these hundred of years. Finally, we analyze some of the challenges of computer performance evaluation appearing today, mainly those related to the energy consumption and sustainability, globally known as Green ICT.

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Compile-time dynamic voltage scaling settings

Cited by 89 publications

References 18 publications

Bounding energy consumption in large-scale MPI programs

Bounding energy consumption in large-scale MPI programs

Exploring multi-threaded Java application performance on multicore hardware

From the Origins of Performance Evaluation to New Green ICT Performance Engineering

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