Performance Validation on Multicore Mobile Devices

Hubbard, Thomas N.; Lencevicius, Raimondas; Metz, Edu; Raghavan, G.

doi:10.1007/978-3-540-69149-5_44

Cited by 6 publications

(6 citation statements)

References 14 publications

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“…The controller will calculate the speedup to be applied (with core and frequency actuation) periodically. Denoting by the time index for said periodic calculation, and assuming that the time span between two subsequent calculations is long enough for the applied speedup to exert all of its action on the plant, the relationship between the speedup and the frame encoding rate (fer) is expressed in the discrete time domain by (1) where is the possibly time varying application workload, i.e., the (nominal) amount of time consumed between two subsequent frame encodings, and an exogenous disturbance accounting for any non nominal time behavior. Of course, is in general unknown but the profiling phase can easily provide a reliable average and bounds for it.…”

Section: Step 2b: Control Designmentioning

confidence: 99%

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Power Optimization in Embedded Systems via Feedback Control of Resource Allocation

Maggio

Hoffmann

Santambrogio

et al. 2013

IEEE Trans. Contr. Syst. Technol.

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Embedded systems often operate in so variable conditions that design can only be carried out for some worst-case scenario. This leads to over-provisioned resources, and undue power consumption. Feedback control is an effective (and not yet fully explored) way to tailor resource usage online, thereby making the system behave and consume as if it was optimized for each specific utilization case. A control-theoretical methodology\ud is here proposed to complement architecture design in a view to said tailoring. Experimental results show that a so addressed architecture meets performance requirements, while consuming less power than any fixed (i.e., uncontrolled) one capable of at taining the same goals. Also, the methodology naturally induces computationally lightweight control laws

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Section: Step 2b: Control Designmentioning

confidence: 99%

“…It could make sense to design a dedicated chip for an old-fashioned mobile phone, while this is apparently meaningless for a modern smartphone [1]. Modern devices are not designed for just one task.…”

Section: Introductionmentioning

confidence: 98%

Power Optimization in Embedded Systems via Feedback Control of Resource Allocation

Maggio

Hoffmann

Santambrogio

et al. 2013

IEEE Trans. Contr. Syst. Technol.

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“…To prolong battery life, most off-the-shelf smartphones and tablets adopt power management schemes that make use of dynamic voltage and frequency scaling (DVFS) [16,18] and processor hot plugging [17]. In [13], the authors have analyzed the effectiveness of various power management schemes for multi-core smartphone systems in terms of energy efficiency and user-perceived response latency. In [14], the authors have created an application framework that allows execution of different types of threads, comparing their efficiency and measuring power consumption on mobile devices.…”

Section: Related Workmentioning

confidence: 99%

A Middleware for Power Management in Multicore Smartphones

Li¹,

Mishra²

2015

Proceedings of the 12th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services

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Increased power consumption is a critical concern for smartphone users. While multi-core processors in smartphones have already emerged in market, current applications are yet to take full advantage of this new architecture, particularly in the area of managing power consumption. This paper addresses the issue of managing power consumption in multicore smartphones via a middleware layer that schedules optimal number of cores for currently running applications taking into account the tradeoff between power consumption, performance and user experience. The paper first describes a simple and accurate method to measure the overall power consumption and then studies the impact of scheduling seven different popular applications over one to four cores on the overall power consumption. Based on this study, the paper proposes three new power-aware scheduling algorithms that dynamically schedule optimal number of cores as well as dynamically adjust the voltage frequency of each online core to achieve the best tradeoff between power consumption, application performance and user experience under the current context. Evaluation from a prototype implementation of the middleware on a quad-core HTC One shows that these algorithms result in significant reduction in power consumption while ensuring good performance and user experience.

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“…1씩 증가시키면서 최대 40회 까지 피보나치수열을 반복 수행하였을 때, 기존의 시스템 (before) 과 제 안한 BioMP (after)의 처리속도를 비교 실험하였 다 [14] . 적임을 알았다 [16] .…”

Section: 애플리케이션의 병렬화unclassified

Task Parallelism System of Application for Multicore-Based Mobile Platform

Lim¹,

Lee²,

Eom³

2013

The Journal of Korean Institute of Communications and Informati

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This paper proposes a task parallelism system (BioMP) to improve applications' execution time of multicore based mobile device. When application developers append the functions of parallel specification into the existing software, our proposed system supports the parallel processing of threads as well as a compatibility. BioMP improves the software in order that an existing large-scale source can recognize the multicore architecture. From our experiment, our idea improved the execution time of application until about 64% against the existing system in multicore environment based on quad core. In addition, BioMP does not require any additional modification of a mobile platform because BioMP is independent component. Consequently, when application developers release multicore-aware applications into the application store, users can immediately run without any modification of the mobile device.

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Performance Validation on Multicore Mobile Devices

Cited by 6 publications

References 14 publications

Power Optimization in Embedded Systems via Feedback Control of Resource Allocation

Power Optimization in Embedded Systems via Feedback Control of Resource Allocation

A Middleware for Power Management in Multicore Smartphones

Task Parallelism System of Application for Multicore-Based Mobile Platform

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