Computing with Memory for Energy-Efficient Robust Systems
Nonfiction, Science & Nature, Technology, Electronics, Circuits
| Author: | Somnath Paul, Swarup Bhunia | ISBN: | 9781461477983 |
| Publisher: | Springer New York | Publication: | September 7, 2013 |
| Imprint: | Springer | Language: | English |
| Author: | Somnath Paul, Swarup Bhunia |
| ISBN: | 9781461477983 |
| Publisher: | Springer New York |
| Publication: | September 7, 2013 |
| Imprint: | Springer |
| Language: | English |
This book analyzes energy and reliability as major challenges faced by designers of computing frameworks in the nanometer technology regime. The authors describe the existing solutions to address these challenges and then reveal a new reconfigurable computing platform, which leverages high-density nanoscale memory for both data storage and computation to maximize the energy-efficiency and reliability. The energy and reliability benefits of this new paradigm are illustrated and the design challenges are discussed. Various hardware and software aspects of this exciting computing paradigm are described, particularly with respect to hardware-software co-designed frameworks, where the hardware unit can be reconfigured to mimic diverse application behavior. Finally, the energy-efficiency of the paradigm described is compared with other, well-known reconfigurable computing platforms.
This book analyzes energy and reliability as major challenges faced by designers of computing frameworks in the nanometer technology regime. The authors describe the existing solutions to address these challenges and then reveal a new reconfigurable computing platform, which leverages high-density nanoscale memory for both data storage and computation to maximize the energy-efficiency and reliability. The energy and reliability benefits of this new paradigm are illustrated and the design challenges are discussed. Various hardware and software aspects of this exciting computing paradigm are described, particularly with respect to hardware-software co-designed frameworks, where the hardware unit can be reconfigured to mimic diverse application behavior. Finally, the energy-efficiency of the paradigm described is compared with other, well-known reconfigurable computing platforms.
