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Record Nr. |
UNINA9910299942703321 |
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Autore |
Pagani Santiago |
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Titolo |
Advanced Techniques for Power, Energy, and Thermal Management for Clustered Manycores / / by Santiago Pagani, Jian-Jia Chen, Muhammad Shafique, Jörg Henkel |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
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ISBN |
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Edizione |
[1st ed. 2018.] |
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Descrizione fisica |
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1 online resource (295 pages) : illustrations |
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Disciplina |
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Soggetti |
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Electronic circuits |
Microprocessors |
Electronics |
Microelectronics |
Circuits and Systems |
Processor Architectures |
Electronics and Microelectronics, Instrumentation |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Introduction -- Background and Related Work -- System Model -- Experimental Framework -- Thermal Safe Power (TSP) -- Transient and Peak Temperature Computation based on Matrix Exponentials (MatEx) -- Selective Boosting for Multicore Systems (seBoost) -- Energy and Peak Power Efficiency Analysis for Simple Approximation Schemes -- Energy-Efficient Task-to-core Assignment for Homogeneous Clustered Manycores -- Energy-Efficient Task-to-core Assignment for Heterogeneous Clustered Manycores -- Conclusions. |
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Sommario/riassunto |
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This book focuses on two of the most relevant problems related to power management on multicore and manycore systems. Specifically, one part of the book focuses on maximizing/optimizing computational performance under power or thermal constraints, while another part focuses on minimizing energy consumption under performance (or real-time) constraints. Provides a comprehensive introduction to energy, power, and temperature management, highlighting the |
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different optimization goals, particularly computational performance, power and energy consumption, and temperature; Highlights the differences and similarities between the two key challenges of performance optimization under power or thermal constraints and energy minimization under performance constraints; Discusses in detail several means that can be used to optimize performance or energy while satisfying the desired constraints, including core heterogeneity, task-to-core assignment/mapping, dynamic power management (DPM), and dynamic voltage and frequency scaling (DVFS). |
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