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Proceedings of the 2003 international workshop on System-level interconnect prediction
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Proceedings of the 2003 international workshop on System-level interconnect prediction
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Proceedings of the 2002 IEEE/ACM international conference on Computer-aided design
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Delay budgeting in sequential circuit with application on FPGA placement
Proceedings of the 40th annual Design Automation Conference
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Proceedings of the 40th annual Design Automation Conference
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Proceedings of the 2003 IEEE/ACM international conference on Computer-aided design
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Proceedings of the 2003 IEEE/ACM international conference on Computer-aided design
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IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Sequential delay budgeting with interconnect prediction
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
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Proceedings of the 2004 IEEE/ACM International conference on Computer-aided design
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Proceedings of the 2004 IEEE/ACM International conference on Computer-aided design
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Probabilistic Delay Budgeting for Soft Realtime Applications
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Proceedings of the 43rd annual Design Automation Conference
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Proceedings of the 2007 international workshop on System level interconnect prediction
Probabilistic delay budget assignment for synthesis of soft real-time applications
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Simultaneous Vtselection and assignment for leakage optimization
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Slack budgeting and slack to length converting for multi-bit flip-flop merging
Proceedings of the Conference on Design, Automation and Test in Europe
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In this paper, we present a new, general approach to the problem of computing upper bounds on net delays. The upper bounds on net delays are computed so that timing constraints between input and output signals are satisfied. The set of delay upper bounds is called a delay budget. The objective of this work is to compute a delay budget that will lead to timing feasible circuit placement and routing. In our formulation, we find a delay budget so that the placement phase has “maximum flexibility.” We formulate this problem as a convex programming problem and prove that it has a special structure. We utilize the special structure of the problem to propose an efficient graph-based algorithm. We present experimental results for our algorithms with the MCNC placement benchmarks. Our experiments use budgeting results as net length constraints for the TimberWolf placement program, which we use to evaluate the budgeting algorithms. We obtain an average of 50% reduction in net length constraint violations over the well-known zero-slack algorithm (ZSA). We also study different delay budgeting objective functions, which yield 2× performance improvements without loss of solution quality. Our results and graph-based formulation show that our proposed algorithm is suitable for modern large-scale budgeting problems