Buch, Englisch, 338 Seiten, Format (B × H): 161 mm x 240 mm, Gewicht: 675 g
Challenges and Vision
Buch, Englisch, 338 Seiten, Format (B × H): 161 mm x 240 mm, Gewicht: 675 g
ISBN: 978-0-367-02344-7
Verlag: CRC Press
Heterogeneous Computing Architectures: Challenges and Vision provides an updated vision of the state-of-the-art of heterogeneous computing systems, covering all the aspects related to their design: from the architecture and programming models to hardware/software integration and orchestration to real-time and security requirements. The transitions from multicore processors, GPU computing, and Cloud computing are not separate trends, but aspects of a single trend-mainstream; computers from desktop to smartphones are being permanently transformed into heterogeneous supercomputer clusters. The reader will get an organic perspective of modern heterogeneous systems and their future evolution.
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Informatik Rechnerarchitektur
- Mathematik | Informatik EDV | Informatik Technische Informatik Grid-Computing & Paralleles Rechnen
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Funktionale, Logische, Parallele und Visuelle Programmierung
- Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Cloud-Computing, Grid-Computing
Weitere Infos & Material
Preface. Acknowledgements. About the Editors. Contributors. Heterogeneous Data Center Architectures: Software&Hardware Integration and Orchestration Aspects. Modular Operating Systems for Large Scale, Distributed and Heterogeneous Environments. Programming and Architecture Models. Simplifying Parallel Programming and Execution for Distributed Heterogeneous Computing Platforms. Design-time Tooling to Guide Programming for Embedded Heterogeneous Hardware Platforms. Middleware, Infrastructure Management and Self-Reconfiguration for Heterogeneous Parallel Architecture Environments. A Novel Framework for Utilising Multi-FPGAs in HPC Systems. A Quantitative Comparison for Image Recognition on Accelerated Heterogeneous Cloud Infrastructures. Machine Learning on Low-Power Low-Cost Platforms: an Application Case Study. Security for Heterogeneous Systems. Real-Time Heterogeneous Platforms. Future Challenges in Heterogeneity. Bibliography. Index