| Summary: | 博士 === 國立臺灣大學 === 資訊工程學研究所 === 94 === While reconfigurable computing is identified as one important direction for future embedded systems design, various challenges exist! In this dissertation, we explore several critical issues in reconfigurable computing: reconfiguration plan derivation, configuration context minimization, dynamic-voltage-scaling energy-efficiency, and embedded operating systems. The minimization problem of configuration contexts is first explored, provided that
deadline and precedence constraints are given. We exploit different constraints on the context minimization problem and their corresponding subproblems. We then propose scheduling algorithms for the derivation of reconfiguration plans based on a given schedule. When no two tasks in a schedule share a processing element, optimal
scheduling algorithms are presented. A heuristic-based scheduling algorithm is proposed for general cases. When dynamic voltage scaling is considered, we propose algorithms to schedule the loadings and the executions of tasks in a multi-context FPGA at run-time. Optimal scheduling algorithms and approximation algorithms are presented for cases in which task partitions over contexts are or are not given. The dissertation is concluded by the proposing of a tiny real-time kernel for embedded systems. The kernel is ported to run over hardware/software co-design tools. A series of experiments was also done to evaluate the kernel performance.
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