scholarly journals Computer Architecture and Design

2001 ◽  
pp. 161-226
Author(s):  
Siamack Haghighi ◽  
Jean-Luc Gaudiot ◽  
Manoj Franklin ◽  
Bruce Jacob ◽  
Lejla Batina ◽  
...  

Author(s):  
Kai-Jung Shih ◽  
Pao-Ann Hsiung

Reconfigurable computing is breaking down the barrier between hardware and software design technologies. The segregation between the two has become more and more fuzzy because reconfigurable computing has now made it possible for hardware to be programmed and software to be synthesized. Reconfigurable computing can also be viewed as a trade-off between general-purpose computing and application specific design. Given the architecture and design flexibility, reconfigurable computing has catalyzed the progress in hardware-software codesign technology and a vast number of application areas such as scientific computing, biological computing, artificial intelligence, signal processing, security computing, and control-oriented design, to name a few. In this article, we briefly introduce why and what is reconfigurable computing in the introduction section. Then, the resulting enhancements of hardware-software codesign methods and the techniques, tools, platforms, design and verification methodologies of reconfigurable computing will be introduced in the background section. Furthermore, we will introduce and compare some reconfigurable computing architectures. Finally, the future trends and conclusions will also be given. This article is aimed at widespread audiences, including both a person not particularly well grounded in computer architecture and a technical person.


1994 ◽  
Vol 33 (01) ◽  
pp. 60-63 ◽  
Author(s):  
E. J. Manders ◽  
D. P. Lindstrom ◽  
B. M. Dawant

Abstract:On-line intelligent monitoring, diagnosis, and control of dynamic systems such as patients in intensive care units necessitates the context-dependent acquisition, processing, analysis, and interpretation of large amounts of possibly noisy and incomplete data. The dynamic nature of the process also requires a continuous evaluation and adaptation of the monitoring strategy to respond to changes both in the monitored patient and in the monitoring equipment. Moreover, real-time constraints may imply data losses, the importance of which has to be minimized. This paper presents a computer architecture designed to accomplish these tasks. Its main components are a model and a data abstraction module. The model provides the system with a monitoring context related to the patient status. The data abstraction module relies on that information to adapt the monitoring strategy and provide the model with the necessary information. This paper focuses on the data abstraction module and its interaction with the model.


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