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Advanced techniques for power, energ...

Pagani, Santiago.

Advanced techniques for power, energy, and thermal management for clustered manycores

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Advanced techniques for power, energy, and thermal management for clustered manycoresby Santiago Pagani ... [et al.].
其他作者:	Pagani, Santiago.
出版者:	Cham :Springer International Publishing :2018.
面頁冊數:	l, 250 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Multiprocessors.
電子資源:	http://dx.doi.org/10.1007/978-3-319-77479-4
ISBN:	9783319774794$q(electronic bk.)

Advanced techniques for power, energy, and thermal management for clustered manycores
Advanced techniques for power, energy, and thermal management for clustered manycores[electronic resource] /by Santiago Pagani ... [et al.]. - Cham :Springer International Publishing :2018. - l, 250 p. :ill., digital ;24 cm.

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.

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 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)

ISBN: 9783319774794$q(electronic bk.)

Standard No.: 10.1007/978-3-319-77479-4doiSubjects--Topical Terms:

210580
Multiprocessors.

LC Class. No.: QA76.5 / .P343 2018

Dewey Class. No.: 004.35

Advanced techniques for power, energy, and thermal management for clustered manycores
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245 0 0 $a Advanced techniques for power, energy, and thermal management for clustered manycores $h [electronic resource] / $c by Santiago Pagani ... [et al.].
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505 0 $a 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.
520 $a 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 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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