Customizable Computing / by Yu-Ting Chen, Jason Cong, Michael Gill, Glenn Reinman
By: Chen, Yu-Ting, (Computer scientist), autor
Contributor(s): Cong, Jason, autor
| Gill, Michael, autor | Reinman, Glenn,, autor
Material type:
E-bookSeries: (Synthesis Lectures on Computer Architecture, 1935-3243).Publisher: Cham : Springer International Publishing, 2015Edition: 1st edition 2015.Description: 1 recurso en línea (XI, 106 páginas).ISBN: 9783031017483.Subject: Arquitectura de ordenador
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
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LIBRO-E NO PRÉSTAMO
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Madrid Digital Acceso Electrónico (UEM) | Ciencias e Ingeniería | QA76.9.A73 2015 EB (Browse shelf(Opens below)) | Acceso electrónico | eBook.01113054 |
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| QA76.9 .A73 2014 EB Optimization and Mathematical Modeling in Computer Architecture | QA76.9.A73 2015 EB Power-Efficient Computer Architectures : Recent Advances | QA76.9.A73 2015 EB Single-Instruction Multiple-Data Execution | QA76.9.A73 2015 EB Customizable Computing | QA76.9.A73 2016 EB Analyzing Analytics | QA76.9.A73 2016 EB Datacenter Design and Management : A Computer Architect's Perspective | QA76.9.A73 2017 EB Fundamentals of computer architecture and design |
Acknowledgments -- Introduction -- Road Map -- Customization of Cores -- Loosely Coupled Compute Engines -- On-Chip Memory Customization -- Interconnect Customization -- Concluding Remarks -- Bibliography -- Authors' Biographies .
Since the end of Dennard scaling in the early 2000s, improving the energy efficiency of computation has been the main concern of the research community and industry. The large energy efficiency gap between general-purpose processors and application-specific integrated circuits (ASICs) motivates the exploration of customizable architectures, where one can adapt the architecture to the workload. In this Synthesis lecture, we present an overview and introduction of the recent developments on energy-efficient customizable architectures, including customizable cores and accelerators, on-chip memory customization, and interconnect optimization. In addition to a discussion of the general techniques and classification of different approaches used in each area, we also highlight and illustrate some of the most successful design examples in each category and discuss their impact on performance and energy efficiency. We hope that this work captures the state-of-the-art research and development on customizable architectures and serves as a useful reference basis for further research, design, and implementation for large-scale deployment in future computing systems.
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