Circuit partitioning for huge logic emulation systems

Author(s):  
Nan-Chi Chou ◽  
Lung-Tien Liu ◽  
Chung-Kuan Cheng ◽  
Wei-Jin Dai ◽  
Rodney Lindelof
VLSI Design ◽  
2000 ◽  
Vol 11 (3) ◽  
pp. 219-235 ◽  
Author(s):  
Huiqun Liu ◽  
Kai Zhu ◽  
D. F. Wong

In this paper, we present an algorithm for circuit partitioning with complex resource constraints in large FPGAs. Traditional partitioning methods estimate the capacity of an FPGA device by counting the number of logic blocks, however this is not accurate with the increasing diverse resource types in the new FPGA architectures. We first propose a network flow based method to optimally check whether a circuit or a subcircuit is feasible for a set of available heterogeneous resources. Then the feasibility checking procedure is integrated in the FM-based algorithm for circuit partitioning. Incremental flow technique is employed for efficient implementation. Experimental results on the MCNC benchmark circuits show that our partitioning algorithm not only yields good results, but also is efficient. Our algorithm for partitioning with complex resource constraints is applicable for both multiple FPGA designs (e.g., logic emulation systems) and partitioning-based placement algorithms for a single large hierarchical FPGA (e.g., Actel's ES6500 FPGA family).


2019 ◽  
Vol 8 (2) ◽  
pp. 5589-5593

A VLSI integrated circuit is the most significant part of electronic systems such as personal computer or workstation, digital camera, cell phone or a portable computing device, and automobile. So development within the field of electronic space depends on the design planning of VLSI integrated circuit. Circuit partitioning is most important step in VLSI physical design process. Many heuristic partitioning algorithms are proposed for this problem. The first heuristic algorithm for hypergraph partitioning in the domain of VLSI is FM algorithm. In this paper, I have proposed three variations of FM algorithm by utilizing pair insightful swapping strategies. I have played out a relative investigation of FM and my proposed algorithms utilizing two datasets for example ISPD98 and ISPD99. Test results demonstrate that my proposed calculations outflank the FM algorithm.


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