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Due to exponential behavior of gate-oxide leakage current with temperature and technology scaling, leakage power plays important role in nano - CMOS circuit. In this paper, we present simultaneous scheduling and binding algorithm for optimizing leakage current during behavioral synthesis. It uses TED (Taylor Expansion Diagram) for generating optimized DFG (Data Flow Graph). Once DFG is obtained, it...
Markov Random Fields (MRFs), a.k.a. Graphical Models, serve as popular models for networks in the social and biological sciences, as well as communications and signal processing. A central problem is one of structure learning or model selection: given samples from the MRF, determine the graph structure of the underlying distribution. When the MRF is not Gaussian (e.g. the Ising model) and contains...
We address the problem of video super resolution - obtaining a single high-resolution video whose spatial and temporal resolutions are higher than any of the input low-resolution videos. We employ a reconstruction based approach using MRF -MAP formalism, and use approximate optimization using graph cuts to carry out the reconstruction. We show that in our formulation it is possible to selectively...
In this paper, we present co-processor selection problem for minimum energy consumption in hw/sw co-design on FPGAs with dual power mode. We provide theoretical analysis for the problem under no constraint, resource constraint, and timing constraint. We prove that the complexity of the problem in each case is NP-Hard and we provide a generalized ILP formulation. We compared the result of our approach...
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