Academic literature on the topic 'Dynamic Voltage and Frequency Scaling (DVFS)'

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Journal articles on the topic "Dynamic Voltage and Frequency Scaling (DVFS)"

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Kocanda, Piotr, and Andrzej Kos. "Energy losses and DVFS effectiveness vs technology scaling." Microelectronics International 32, no. 3 (2015): 158–63. http://dx.doi.org/10.1108/mi-01-2015-0008.

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Purpose – This article aims to present complete analysis of energy losses in complementary metal-oxide semiconductor (CMOS) circuits and the effectiveness of dynamic voltage and frequency scaling (DVFS) as a method of energy conservation in CMOS circuits in variety of technologies. Energy efficiency in CMOS devices is an issue of highest importance with still continuing technology scaling. There are powerful tools for energy conservation in form of dynamic voltage scaling (DVS) and dynamic frequency scaling (DFS). Design/methodology/approach – Using analytical equations and Spice models of var
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Panda, Prasanta, Aruna Tripathy, and Kanhu Charan Bhuyan. "Accurate Load Prediction in Dynamic Voltage Frequency Scaling Systems." Journal of Integrated Circuits and Systems 20, no. 1 (2025): 1–14. https://doi.org/10.29292/jics.v20i1.977.

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Dynamic Voltage and Frequency Scaling (DVFS) is a potent technique employed to minimize dynamic power consumption in Silicon on Chips (SoCs). The accurate determination of future loads is pivotal in DVFS systems, as it influences the selection of desired frequencies and optimal voltages while ensuring circuit performance is not compromised. In this paper, we introduce a novel approach and algorithm for precise future load determination in processors for DVFS systems using Machine Learning Time Series Method. Our proposed algorithm dynamically evaluates various models from the model repository,
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Xu, Shen, Jun Song Li, and Jian Feng Jiang. "Dynamic Voltage and Frequency Scaling Under an Accurate System Energy Model." Advanced Materials Research 442 (January 2012): 321–25. http://dx.doi.org/10.4028/www.scientific.net/amr.442.321.

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Dynamic voltage and frequency scaling (DVFS) is a technique used in modern portable devices operated by battery to set voltage and frequency levels that meet performance requirements while minimizing energy consumption. Most of the present work on DVFS policies are based on simplistic assumptions about the hardware characteristics. In this paper, we discuss the DVFS problem under an accurate system energy model which comes from a application system portable media player (PMP) with a DVFS-capable processor PXA255. We present an optimal DVFS algorithm based on all frequency combinations at the c
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Liang, Wen Yew, Ming Feng Chang, Yen Lin Chen, and Jenq Haur Wang. "Performance Evaluation for Dynamic Voltage and Frequency Scaling Using Runtime Performance Counters." Applied Mechanics and Materials 284-287 (January 2013): 2575–79. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.2575.

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Dynamic voltage and frequency scaling (DVFS) is an effective technique for reducing power consumption. The system performance is not easy to evaluate through Dynamic Voltage and Frequency Scaling. Most of studies use the execution time as an indicator while measuring the performance. However, DVFS adjusted processor speed during a fixed-length period so it cannot rely on the execution time to evaluate the system performance. This study proposes a novel and simple performance evaluation method to evaluate the system performance when DVFS is activated. Based on the performance evaluation method,
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Hassan, Hasliza, Mohd Shahrul Izwan Akhball, Noraini Marsi, Nabihah @Nornabihah binti Ahmad, and Warsuzarina binti Mat Zubadi. "Analysis of ALU Performance with Dynamic Voltage and Frequency Scaling Technique and Clock Gating." Journal of Physics: Conference Series 3020, no. 1 (2025): 012005. https://doi.org/10.1088/1742-6596/3020/1/012005.

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Abstract The Arithmetic Logic Unit (ALU) is a critical component of modern mad processors that handles arithmetic and logic operations. As power efficiency becomes more important in both high-performance and energy-constrained computing systems, Dynamic Voltage and Frequency Scaling (DVFS) and Clock Gating was emerged as approach for lowering power consumption. Therefore, this paper presenting the ALU design in both techniques, while maintaining acceptable performance. This paper shows the design finding of ALU performance with DVFS technique and Clock Gating technique. All this design was don
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Gendler, Alex, Ernest Knoll, and Yiannakis Sazeides. "I-DVFS: Instantaneous Frequency Switch During Dynamic Voltage and Frequency Scaling." IEEE Micro 41, no. 5 (2021): 76–84. http://dx.doi.org/10.1109/mm.2021.3096655.

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Florence, A. Paulin, V. Shanthi, and C. B. Sunil Simon. "Energy Conservation Using Dynamic Voltage Frequency Scaling for Computational Cloud." Scientific World Journal 2016 (2016): 1–13. http://dx.doi.org/10.1155/2016/9328070.

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Cloud computing is a new technology which supports resource sharing on a “Pay as you go” basis around the world. It provides various services such as SaaS, IaaS, and PaaS. Computation is a part of IaaS and the entire computational requests are to be served efficiently with optimal power utilization in the cloud. Recently, various algorithms are developed to reduce power consumption and even Dynamic Voltage and Frequency Scaling (DVFS) scheme is also used in this perspective. In this paper we have devised methodology which analyzes the behavior of the given cloud request and identifies the asso
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Jia, Fan, and Longbing Zhang. "Fine-Grained CPU Power Management Based on Digital Frequency Divider." Electronics 12, no. 2 (2023): 407. http://dx.doi.org/10.3390/electronics12020407.

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Dynamic voltage and frequency scaling (DVFS) is a widely used method to improve the energy efficiency of the CPU. Reducing the voltage and frequency during memory-intensive workloads can minimize power consumption without affecting performance, thereby improving overall energy efficiency. A finer-grained DVFS strategy leads to better energy efficiency. However, due to the limitation of voltage regulators, the implementation granularity of the current DVFS strategies is 100 μs or more. This paper proposes that managing the CPU’s power through a more fine-grained load-aware approach can improve
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Chen, Yen-Lin, Ming-Feng Chang, Chao-Wei Yu, Xiu-Zhi Chen, and Wen-Yew Liang. "Learning-Directed Dynamic Voltage and Frequency Scaling Scheme with Adjustable Performance for Single-Core and Multi-Core Embedded and Mobile Systems." Sensors 18, no. 9 (2018): 3068. http://dx.doi.org/10.3390/s18093068.

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Dynamic voltage and frequency scaling (DVFS) is a well-known method for saving energy consumption. Several DVFS studies have applied learning-based methods to implement the DVFS prediction model instead of complicated mathematical models. This paper proposes a lightweight learning-directed DVFS method that involves using counter propagation networks to sense and classify the task behavior and predict the best voltage/frequency setting for the system. An intelligent adjustment mechanism for performance is also provided to users under various performance requirements. The comparative experimenta
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Sabri, Sharizal Fadlie, Noor Azurati Ahmad, Shamsul Sahibuddin, and Rudzidatul Dziyauddin. "Dynamic frequency scheduling for CubeSat's on-board and data handling subsystem." Indonesian Journal of Electrical Engineering and Computer Science 22, no. 3 (2021): 1672–78. https://doi.org/10.11591/ijeecs.v22.i3.pp1672-1678.

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CubeSat is a small-sized satellite that provides a cheaper option for the manufacturer to have a fully operational satellite. Due to its size, CubeSat can only generate limited power, and this will restrict its functionality. This research aims to improve CubeSat’s power consumption by implementing the dynamic voltage and frequency scaling (DVFS) technique to on-board and data handling subsystem (OBDH). DVFS will find the best operating frequency to execute all of OBDH’s task. This paper explains how we determined the task set, representing all routine tasks performed by OBDH durin
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Dissertations / Theses on the topic "Dynamic Voltage and Frequency Scaling (DVFS)"

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Rountree, Barry. "Theory and Practice of Dynamic Voltage/Frequency Scaling in the High Performance Computing Environment." Diss., The University of Arizona, 2009. http://hdl.handle.net/10150/305368.

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This dissertation provides a comprehensive overview of the theory and practice of Dynamic Voltage/Frequency Scaling (DVFS) in the High Performance Computing (HPC) environment. We summarize the overall problem as follows: how can the same level of computational performance be achieved using less electrical power? Equivalently, how can computational performance be increased using the same amount of electrical power? In this dissertation we present performance and architecture models of DVFS as well as the Adagio runtime system. The performance model recasts the question as an optimization proble
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Saha, Sonal. "An Experimental Evaluation of Real-Time DVFS Scheduling Algorithms." Thesis, Virginia Tech, 2011. http://hdl.handle.net/10919/35035.

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Dynamic voltage and frequency scaling (DVFS) is an extensively studied energy manage- ment technique, which aims to reduce the energy consumption of computing platforms by dynamically scaling the CPU frequency. Real-Time DVFS (RT-DVFS) is a branch of DVFS, which reduces CPU energy consumption through DVFS, while at the same time ensures that task time constraints are satisfied by constructing appropriate real-time task schedules. The literature presents numerous RT-DVFS scheduling algorithms, which employ different tech- niques to utilize the CPU idle time to scale the frequency. Many of these
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Clark, Mark A. "Dynamic Voltage/Frequency Scaling and Power-Gating of Network-on-Chip with Machine Learning." Ohio University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1544105215810566.

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Li, Juan. "Application-Directed DVFS using Multiple Clock Domains on Graphics Hardware." Digital WPI, 2009. https://digitalcommons.wpi.edu/etd-theses/85.

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As handheld devices have become increasingly popular, powerful programmable graphics hardware for mobile and handheld devices has been deployed. While many resources on mobile devices are limited, the predominant problem for mobile devices is their limited battery power. Several techniques have been proposed to increase the energy efficiency of mobile applications and improve battery life. In this thesis, we propose a new dynamic voltage and frequency scaling (DVFS) on Graphics Processing Units (GPU). In most cases, cues within the graphics appli- cation can be used to predict portions of a GP
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Muhammad, F. "Ordonnancement de tâches efficace et à complexité maîtrisée pour des systèmes temps-réel." Phd thesis, Université de Nice Sophia-Antipolis, 2009. http://tel.archives-ouvertes.fr/tel-00454616.

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Les performances des algorithmes d'ordonnancement ont un impact direct sur les performances du système complet. Les algorithmes d'ordonnancement temps réel possèdent des bornes théoriques d'ordonnançabilité optimales mais cette optimalité est souvent atteinte au prix d'un nombre élevé d'événements d'ordonnancement à considérer (préemptions et migrations de tâches) et d'une complexité algorithmique importante. Notre opinion est qu'en exploitant plus efficacement les paramètres des tâches il est possible de rendre ces algorithmes plus efficaces et à coût maitrisé, et ce dans le but d'améliorer l
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Shiomi, Jun. "Performance Modeling and On-Chip Memory Structures for Minimum Energy Operation in Voltage-Scaled LSI Circuits." Kyoto University, 2017. http://hdl.handle.net/2433/228252.

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Bhatti, K. "Energy-aware Scheduling for Multiprocessor Real-time Systems." Phd thesis, Université de Nice Sophia-Antipolis, 2011. http://tel.archives-ouvertes.fr/tel-00599980.

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Les applications temps réel modernes deviennent plus exigeantes en termes de ressources et de débit amenant la conception d'architectures multiprocesseurs. Ces systèmes, des équipements embarqués au calculateur haute performance, sont, pour des raisons d'autonomie et de fiabilité, confrontés des problèmes cruciaux de consommation d'énergie. Pour ces raisons, cette thèse propose de nouvelles techniques d'optimisation de la consommation d'énergie dans l'ordonnancement de systèmes multiprocesseur. La premiére contribution est un algorithme d'ordonnancement hiérarchique á deux niveaux qui autorise
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Mallangi, Siva Sai Reddy. "Low-Power Policies Based on DVFS for the MUSEIC v2 System-on-Chip." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-229443.

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Multi functional health monitoring wearable devices are quite prominent these days. Usually these devices are battery-operated and consequently are limited by their battery life (from few hours to a few weeks depending on the application). Of late, it was realized that these devices, which are currently being operated at fixed voltage and frequency, are capable of operating at multiple voltages and frequencies. By switching these voltages and frequencies to lower values based upon power requirements, these devices can achieve tremendous benefits in the form of energy savings. Dynamic Voltage a
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Akgul, Yeter. "Gestion de la consommation basée sur l’adaptation dynamique de la tension, fréquence et body bias sur les systèmes sur puce en technologie FD-SOI." Thesis, Montpellier 2, 2014. http://www.theses.fr/2014MON20132/document.

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Au-delà du nœud technologique CMOS BULK 28nm, certaines limites ont été atteintes dans l'amélioration des performances en raison notamment d'une consommation énergétique devenant trop importante. C'est une des raisons pour lesquelles de nouvelles technologies ont été développées, notamment celles basées sur Silicium sur Isolant (SOI). Par ailleurs, la généralisation des architectures complexes de type multi-cœurs, accentue le problème de gestion de la consommation à grain-fin. Les technologies CMOS FD-SOI offrent de nouvelles opportunités pour la gestion de la consommation en permettant d'ajus
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Zorello, Ligia Maria Moreira. "Dynamic CPU frequency scaling using machine learning for NFV applications." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/3/3141/tde-30012019-100044/.

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Growth in the Information and Communication Technology sector is increasing the need to improve the quality of service and energy efficiency, as this industry has already surpassed 12% of global energy consumption in 2017. Data centers correspond to a large part of this consumption, accounting for about 15% of energy expenditure on the Information and Communication Technology domain; moreover, the subsystem that generates the most costs for data center operators is that of servers and storage. Many solutions have been proposed to reduce server consumption, such as the use of dynamic voltage an
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Books on the topic "Dynamic Voltage and Frequency Scaling (DVFS)"

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Trescases, Olivier. A high-frequency, soft-switching DC-DC converter for dynamic voltage scaling in VLSI loads. 2004.

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Book chapters on the topic "Dynamic Voltage and Frequency Scaling (DVFS)"

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Kumar, Sachin, Saurabh Pal, Satya Singh, et al. "Energy Efficient Model for Balancing Energy in Cloud Datacenters Using Dynamic Voltage Frequency Scaling (DVFS) Technique." In Proceedings of Third Doctoral Symposium on Computational Intelligence. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-3148-2_45.

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Moons, Bert, and Marian Verhelst. "DVAFS—Dynamic-Voltage-Accuracy-Frequency-Scaling Applied to Scalable Convolutional Neural Network Acceleration." In System-Scenario-based Design Principles and Applications. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-20343-6_5.

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Hsu, Chung-Hsing, and Ulrich Kremer. "Dynamic Voltage and Frequency Scaling for Scientific Applications." In Languages and Compilers for Parallel Computing. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-35767-x_6.

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Hsu, Chung-Hsing, and Ulrich Kremer. "Compiler-Directed Dynamic CPU Frequency and Voltage Scaling." In Designing Embedded Processors. Springer Netherlands, 2007. http://dx.doi.org/10.1007/978-1-4020-5869-1_14.

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Akgün, Gökhan, Lester Kalms, and Diana Göhringer. "Resource Efficient Dynamic Voltage and Frequency Scaling on Xilinx FPGAs." In Applied Reconfigurable Computing. Architectures, Tools, and Applications. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44534-8_14.

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Meijer, Maurice, and José Pineda Gyvez. "Technological Boundaries of Voltage and Frequency Scaling for Power Performance Tuning." In Adaptive Techniques for Dynamic Processor Optimization. Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-76472-6_2.

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Patil, Aditya, and Shankaranarayana Bhat M. "Dynamic Voltage and Frequency Scaling Implementation for System-Level Power Reduction." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-4650-7_7.

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Ghosh, Shreya, and Jaydeep Das. "Dynamic Voltage and Frequency Scaling Approach for Processing Spatio-Temporal Queries in Mobile Environment." In Green Mobile Cloud Computing. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08038-8_9.

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Huang, Xin, KenLi Li, and RenFa Li. "A Energy Efficient Scheduling Base on Dynamic Voltage and Frequency Scaling for Multi-core Embedded Real-Time System." In Algorithms and Architectures for Parallel Processing. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03095-6_14.

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Hayamizu, Yuto, Kazuo Goda, Miyuki Nakano, and Masaru Kitsuregawa. "Application-Aware Power Saving for Online Transaction Processing Using Dynamic Voltage and Frequency Scaling in a Multicore Environment." In Architecture of Computing Systems - ARCS 2011. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19137-4_5.

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Conference papers on the topic "Dynamic Voltage and Frequency Scaling (DVFS)"

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Garg, Deepak, and Rajender Sharma. "Low Power Multiplier using Dynamic Voltage and Frequency Scaling (DVFS)." In 2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE, 2014. http://dx.doi.org/10.1109/icacci.2014.6968494.

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Jeabin Lee, Byeong-Gyu Nam, and Hoi-Jun Yoo. "Dynamic Voltage and Frequency Scaling (DVFS) scheme for multi-domains power management." In 2007 IEEE Asian Solid-State Circuits Conference. IEEE, 2007. http://dx.doi.org/10.1109/asscc.2007.4425705.

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Chen, Yen-Hao, Yi-Lun Tang, Yi-Yu Liu, Allen C.-H. Wu, and TingTing Hwang. "A Novel Cache-Utilization Based Dynamic Voltage Frequency Scaling (DVFS) Mechanism for Reliability Enhancements." In Proceedings of the 2016 Design, Automation & Test in Europe Conference & Exhibition (DATE). Research Publishing Services, 2016. http://dx.doi.org/10.3850/9783981537079_0067.

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Melo, Renato, and Vinicius Petrucci. "Eficiência Energética em Navegação Web usando DVFS." In Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos. Sociedade Brasileira de Computação - SBC, 2018. http://dx.doi.org/10.5753/sbrc.2018.2412.

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O consumo de energia tornou-se uma grande preocupação em data centers e dispositivos móveis. Este trabalho propõe um gerenciador inteligente de energia, Web Governor, que explora a técnica DVFS (Dynamic Voltage and Frequency Scaling) disponível em processadores modernos para reduzir o consumo de energia em aplicações de navegação na Web, com o diferencial em explorar características da rede de comunicação. Resultados experimentais mostram que o Web Governor é capaz de reduzir o consumo de energia do sistema em 12% (média) e 18% (max) quando comparado ao governor DVFS do Linux desenvolvido pelo
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Costa, Mariana, Sandro Marques, Thiarles Medeiros, et al. "PampaFreq: Otimizando o EDP de Aplicações Paralelas em Processadores AMD." In XXI Simpósio em Sistemas Computacionais de Alto Desempenho. Sociedade Brasileira de Computação, 2020. http://dx.doi.org/10.5753/wscad.2020.14057.

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O DVFS (Dynamic Voltage and Frequency Scaling) tem sido amplamente utilizado para melhorar o uso dos recursos computacionais quando aplicações paralelas estão sendo executadas. No entanto, as aplicações paralelas têm comportamentos distintos e se relacionam de diferentes maneiras com as políticas de modificação de frequência do DVFS. Neste sentido, é necessário utilizar métodos otimizados de DVFS para melhorar o custo-benefício entre desempenho e consumo de energia, representado pelo EDP (energy-delay product). Dito isso, através de uma extensa exploração de espaço e projeto de diferentes polít
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Chen, Yen-Ming, Ching-Jan Chen, and Yu-Lin Chao. "A Master-Slave Distributed Power Management Architecture for Dynamic Voltage and Frequency Scaling (DVFS) for Low Power Microprocessor." In 2024 IEEE Applied Power Electronics Conference and Exposition (APEC). IEEE, 2024. http://dx.doi.org/10.1109/apec48139.2024.10509029.

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Zhao, Shuze, Ibrahim Ahmed, Carl Lamoureux, Ashraf Lotfi, Vaughn Betz, and Olivier Trescases. "A universal self-calibrating Dynamic Voltage and Frequency Scaling (DVFS) scheme with thermal compensation for energy savings in FPGAs." In 2016 IEEE Applied Power Electronics Conference and Exposition (APEC). IEEE, 2016. http://dx.doi.org/10.1109/apec.2016.7468125.

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Moons, Bert, Roel Uytterhoeven, Wim Dehaene, and Marian Verhelst. "DVAFS: Trading computational accuracy for energy through dynamic-voltage-accuracy-frequency-scaling." In 2017 Design, Automation & Test in Europe Conference & Exhibition (DATE). IEEE, 2017. http://dx.doi.org/10.23919/date.2017.7927038.

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Ait El Mahjoub, Youssef, Leo Le Corre, and Hind Castel-Taleb. "Stochastic Modeling And Optimization For Power And Performance Control In DVFS Systems." In 37th ECMS International Conference on Modelling and Simulation. ECMS, 2023. http://dx.doi.org/10.7148/2023-0497.

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The paper addresses the problem of performance-energy trade-off in DVFS (Dynamic Voltage Frequency Scaling) systems. We propose a stochastic hybrid model between hysteresis models and server block models. We provide a closed form for the steady-state distribution probability and we establish a "st" type order to compare the performance measures. The fast computation of power and performance measures leads to a multi-objective optimization analysis in two forms: a scalarization method and a Pareto based method. For the two approaches, we propose fast and efficient approximate algorithms that co
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Nobuaki Kobayashi and Tadayoshi Enomoto. "A low power 90-nm CMOS motion estimation processor implementing dynamic voltage and frequency scaling (DVFS) and fast motion estimation algorithm." In 2008 IEEE International Symposium on Circuits and Systems - ISCAS 2008. IEEE, 2008. http://dx.doi.org/10.1109/iscas.2008.4541757.

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