Optimal graph constraint reduction for symbolic layout compaction
DAC '93 Proceedings of the 30th international Design Automation Conference
OSCAR: optimum simultaneous scheduling, allocation and resource binding based on integer programming
EURO-DAC '94 Proceedings of the conference on European design automation
DAC '95 Proceedings of the 32nd annual ACM/IEEE Design Automation Conference
Time-constrained code compaction for DSPs
ISSS '95 Proceedings of the 8th international symposium on System synthesis
An exact methodology for scheduling in a 3D design space
ISSS '95 Proceedings of the 8th international symposium on System synthesis
A system level design methodology for the optimization of heterogeneous multiprocessors
ISSS '95 Proceedings of the 8th international symposium on System synthesis
EURO-DAC '96/EURO-VHDL '96 Proceedings of the conference on European design automation
MILP based task mapping for heterogeneous multiprocessor systems
EURO-DAC '96/EURO-VHDL '96 Proceedings of the conference on European design automation
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Optimal Code Placement of Embedded Software for Instruction Caches
EDTC '96 Proceedings of the 1996 European conference on Design and Test
An Automatic Hardware-Software Partitioner Based on the Possibilistic Programming.
EDTC '96 Proceedings of the 1996 European conference on Design and Test
Hardware/Software Partitioning using Integer Programming
EDTC '96 Proceedings of the 1996 European conference on Design and Test
Scheduling using mixed arithmetic: an ILP formulation
EDTC '97 Proceedings of the 1997 European conference on Design and Test
A linear-time heuristic for improving network partitions
DAC '82 Proceedings of the 19th Design Automation Conference
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
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Integer Linear Programming (ILP) is commonly used in high level and system level synthesis. It is an NP-Complete problem (in general cases). There exists some tools that give an optimal solution for small ILP formulations. Nevertheless, these tools may not give solutions for complex formulations. In this paper, we present a solution to overcome the problem of complexity in ILP formulations. We propose a partitioning methodology based on a constraint graph representing all the constraints included in any ILP formulation. To direct the partitioning, the constraint graph nodes are grouped to represent Data Flow Graph (DFG) nodes. This reduced constraint graph can be used to partition any ILP formulation based on DFG. We illustrate this method on ILP formulation for scheduling. Results on ILP scheduling formulations are promising.