The primary aim of this book is to provide a timely and coherent account of the recent advances in many-core computing research. Starting with programming models, operating systems and their applications; it presents runtime management techniques, followed by system modelling, verification and testing methods, and architectures and systems.
The primary aim of this book is to provide a timely and coherent account of the recent advances in many-core computing research. Starting with programming models, operating systems and their applications; it presents runtime management techniques, followed by system modelling, verification and testing methods, and architectures and systems.
1. Part I: Programming models, OS and applications * Chapter 1: HPC with many core processors * Chapter 2: From irregular heterogeneous software to reconfigurable hardware * Chapter 3: Operating systems for many-core systems * Chapter 4: Decoupling the programming model from resource management in throughput processors * Chapter 5: Tools and workloads for many-core computing * Chapter 6: Hardware and software performance in deep learning 2. Part II: Runtime management * Chapter 7: Adaptive-reflective middleware for power and energy management in many-core heterogeneous systems * Chapter 8: Advances in power management of many-core processors * Chapter 9: Runtime thermal management of many-core systems * Chapter 10: Adaptive packet processing on CPU-GPU heterogeneous platforms * Chapter 11: From power-efficient to power-driven computing 3. Part III: System modelling, verification, and testing * Chapter 12: Modelling many-core architectures * Chapter 13: Power modelling of multicore systems * Chapter 14: Developing portable embedded software for multicore systems through formal abstraction and refinement * Chapter 15: Self-testing of multicore processors * Chapter 16: Advances in hardware reliability of reconfigurable many-core embedded systems 4. Part IV: Architectures and systems * Chapter 17: Manycore processor architectures * Chapter 18: Silicon photonics enabled rack-scale many-core systems * Chapter 19: Cognitive I/O for 3D-integrated many-core system * Chapter 20: Approximate computing across the hardware and software stacks * Chapter 21: Many-core systems for big-data computing * Chapter 22: Biologically-inspired massively-parallel computing
1. Part I: Programming models, OS and applications * Chapter 1: HPC with many core processors * Chapter 2: From irregular heterogeneous software to reconfigurable hardware * Chapter 3: Operating systems for many-core systems * Chapter 4: Decoupling the programming model from resource management in throughput processors * Chapter 5: Tools and workloads for many-core computing * Chapter 6: Hardware and software performance in deep learning 2. Part II: Runtime management * Chapter 7: Adaptive-reflective middleware for power and energy management in many-core heterogeneous systems * Chapter 8: Advances in power management of many-core processors * Chapter 9: Runtime thermal management of many-core systems * Chapter 10: Adaptive packet processing on CPU-GPU heterogeneous platforms * Chapter 11: From power-efficient to power-driven computing 3. Part III: System modelling, verification, and testing * Chapter 12: Modelling many-core architectures * Chapter 13: Power modelling of multicore systems * Chapter 14: Developing portable embedded software for multicore systems through formal abstraction and refinement * Chapter 15: Self-testing of multicore processors * Chapter 16: Advances in hardware reliability of reconfigurable many-core embedded systems 4. Part IV: Architectures and systems * Chapter 17: Manycore processor architectures * Chapter 18: Silicon photonics enabled rack-scale many-core systems * Chapter 19: Cognitive I/O for 3D-integrated many-core system * Chapter 20: Approximate computing across the hardware and software stacks * Chapter 21: Many-core systems for big-data computing * Chapter 22: Biologically-inspired massively-parallel computing
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