Pagani, Santiago.
Advanced Techniques for Power, Energy, and Thermal Management for Clustered Manycores [electronic resource] / by Santiago Pagani, Jian-Jia Chen, Muhammad Shafique, Jörg Henkel. - 1st ed. 2018. - L, 250 p. 116 illus., 1 illus. in color. online resource.
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).
9783319774794
10.1007/978-3-319-77479-4 doi
Electronic circuits.
Microprocessors.
Computer architecture.
Electronics.
Electronic Circuits and Systems.
Processor Architectures.
Electronics and Microelectronics, Instrumentation.
TK7867-7867.5
621.3815
Advanced Techniques for Power, Energy, and Thermal Management for Clustered Manycores [electronic resource] / by Santiago Pagani, Jian-Jia Chen, Muhammad Shafique, Jörg Henkel. - 1st ed. 2018. - L, 250 p. 116 illus., 1 illus. in color. online resource.
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).
9783319774794
10.1007/978-3-319-77479-4 doi
Electronic circuits.
Microprocessors.
Computer architecture.
Electronics.
Electronic Circuits and Systems.
Processor Architectures.
Electronics and Microelectronics, Instrumentation.
TK7867-7867.5
621.3815