Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  addresses the problem of estimating lor bounds on the por consumption in scheduled data flow graphs with a fixed number of allocated resources prior to binding. The estimated bound takes into account the effects of resource sharing. It is shown that by introducing Lagrangian multipliers and relaxing the low por binding problem to the assignment problem, which can be solved in O(n/sup 3/), a tight and fast computable bound is achievable. Experimental results show the good quality of the bound. In most cases, deviations smaller than 5% from the optimal binding re observed. The proposed technique can for example be applied in branch and bound high-level synthesis algorithms for efficient pruning of the design space. The estimated lor bound can also be used as a starting point for low por binding heuristics to find optimal or near optimal binding solutions.
['Lars Kruse', 'Eike Schmidt', 'Gerd Jochens', 'Ansgar Stammermann', 'Wolfgang Nebel']
I am writing a research paper on a idea Lower bound estimation for low power high-level synthesis
[{"from": "human", "value": "I am writing a research paper on a idea Lower bound estimation for low power high-level synthesis"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  addresses the problem of estimating lor bounds on the por consumption in scheduled data flow graphs with a fixed number of allocated resources prior to binding. The estimated bound takes into account the effects of resource sharing. It is shown that by introducing Lagrangian multipliers and relaxing the low por binding problem to the assignment problem, which can be solved in O(n/sup 3/), a tight and fast computable bound is achievable. Experimental results show the good quality of the bound. In most cases, deviations smaller than 5% from the optimal binding re observed. The proposed technique can for example be applied in branch and bound high-level synthesis algorithms for efficient pruning of the design space. The estimated lor bound can also be used as a starting point for low por binding heuristics to find optimal or near optimal binding solutions."}]