TAILIEUCHUNG - High Level Synthesis: from Algorithm to Digital Circuit- P27

High Level Synthesis: from Algorithm to Digital Circuit- P27: This book presents an excellent collection of contributions addressing different aspects of high-level synthesis from both industry and academia. "High-Level Synthesis: from Algorithm to Digital Circuit" should be on each designer's and CAD developer's shelf, as well as on those of project managers who will soon embrace high level design and synthesis for all aspects of digital system design. | 13 Operation Scheduling Algorithms and Applications 249 are needed. It is not clear as to which solution is better. Nor is it clear on the order that we should perform scheduling and allocation. Obviously one possible method of design space exploration is to vary the constraints to probe for solutions in a point-by-point manner. For instance you can use some time constrained algorithm iteratively where each iteration has a different input latency. This will give you a number of solutions and their various resource allocations over a set of time points. Or you can run some resource constrained algorithm iteratively. This will give you a latency for each of these area constraints. Design space exploration problem has been the focus in numerous studies. Though it is possible to formulate the problems using Integer Linear Program ILP they quickly become intractable when the problem sizes get large. Much research has been done to cleverly use heuristic approaches to address these problems. Actually one major motivation of the popularly used Force Directed Scheduling FDS algorithm 34 was to address the design space exploration task . by performing FDS to solve a series timing constrained scheduling problems. In the same paper the authors also proposed a method called force-directed list scheduling FDLS to address the resource constrained scheduling problem. The FDS method is constructive since the solution is computed without backtracking. Every decision is made deterministically in a greedy manner. If there are two potential assignments with the same cost the FDS algorithm cannot accurately estimate the best choice. Moreover FDS does not take into account future assignments of operators to the same control step. Consequently it is possible that the resulting solution will not be optimal due to it s greedy nature. FDS works well on small sized problems however it often results to inferior solutions for more complex problems. This phenomena is observed in our .

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