Optimal floorplan area optimization

Wang, T.-C.; Wong, D.F.

doi:10.1109/43.149770

Cited by 67 publications

(40 citation statements)

References 7 publications

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“…This work also stresses the need to use binary trees within this framework since the orders of complexity that arise when using other higher order trees tend to be exponential, which is also referred to in [7] amongst others.…”

Section: Discussionmentioning

confidence: 92%

“…Letusassumethat(a*,b*)8 (7).If(a*,b*)is a dominated solution and using Lemma 1, there must be at least one element of J"(S) that dominates this pair, that is, But as ~0 is nondecreasing in both arguments, this implies that…”

Section: Amc Almeida Et Ul/european Journal Of Operational Researmentioning

confidence: 99%

“…In 1990, a work due to Wang and Wong [7] presented an extension of the previous one, where Stockmeyer's algorithm is extended to solve a slightly more general problem, involving the use of a special kind of floorplans, hierarchical~oorplans of order5 that have nonslicing subfloorplans with five modules called wheels. In order to optimize the area occupied by wheels, they reduce the corresponding hierarchical representation to a binary tree and apply to this tree special procedures to handle its compaction (and which can be extended for wheels of higher order), while using the algorithm of Stockmeyer for normal slicing floorplans.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimal cutting directions and rectangle orientation algorithm

Almeida

Martins

Rodrigues

1998

European Journal of Operational Research

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The first stage in hierarchical approaches to Floorplan Design defines topological relations between components that intend to optimize a given objective in a circuit board. These relations determine a placement that is subsequently optimized in order to minimize a cost measurement (that will probably be one between chip area or perimeter). The board optimization gives rise to multiple subproblems that need to be answered in order to obtain a good solution. Among the most relevant ones we find the problem of defining the optimal orientation of cells and the definition of the optimal cutting sequence that minimize the placement board area. We will present a generalization of an algorithm due to Stockmeyer so that it obtains a solution that not only defines the optimal cell orientation but also the slicing cuts sequence that will lead to this optimal orientation and overall area minimization. 0 1998 Elsevier Science B.V.

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Section: Discussionmentioning

confidence: 92%

Section: Amc Almeida Et Ul/european Journal Of Operational Researmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimal cutting directions and rectangle orientation algorithm

Almeida

Martins

Rodrigues

1998

European Journal of Operational Research

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“…As a result, each sub-problem was solved optimally, but the optimality of the solution on the original problem was not guaranteed. Both Pan et al [6] and Wang et al [7] tried to extend the slicing tree and shape curve representations to handle nonslicing floorplan. But their extensions are limited to some specific nonslicing structures.…”

Section: A Previous Workmentioning

confidence: 99%

SDS: An Optimal Slack-Driven Block Shaping Algorithm for Fixed-Outline Floorplanning

Yan

Chu

2013

IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

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Abstract-This paper presents an efficient, scalable, and optimal slack-driven shaping algorithm for soft blocks in nonslicing floorplan. The proposed algorithm is called SDS. SDS is specifically formulated for fixed-outline floorplanning. Given a fixed upper bound on the layout width, SDS minimizes the layout height by only shaping the soft blocks in the design. Iteratively, SDS shapes some soft blocks to minimize the layout height with the guarantee that the layout width would not exceed the given upper bound. Rather than using some simple heuristic as in previous work, the amount of change on each block is determined by systematically distributing the global total amount of available slack to individual block. During the whole shaping process, the layout height monotonically reduces and eventually converges to an optimal solution. Two optimality conditions are presented to check the optimality of a shaping solution for fixedoutline floorplanning. In practice, to terminate the process of convergence early, we propose two different stopping criteria. We also extend SDS to handle other floorplanning problems, e.g., classical floorplanning. To validate the efficiency and effectiveness of SDS, comprehensive experiments are conducted on MCNC and HB benchmarks. Compared with previous work, SDS achieves the best experimental result with a significantly faster runtime.Index Terms-Block shaping, fixed-outline floorplanning, very large scale integration physical design.

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“…Both Pan et al [5] and Wang et al [6] tried to extend the slicing tree and shape curve representations to handle non-slicing floorplan. But their extensions are limited to some specific nonslicing structures.…”

Section: Previous Workmentioning

confidence: 99%

Optimal slack-driven block shaping algorithm in fixed-outline floorplanning

Yan

Chu

2012

Proceedings of the 2012 ACM International Symposium on International Symposium on Physical Design

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This paper presents an efficient, scalable and optimal slack-driven shaping algorithm for soft blocks in non-slicing floorplan. The proposed algorithm is called SDS. Different from all previous approaches, SDS is specifically formulated for fixed-outline floorplanning. Given a fixed upper bound on the layout width, SDS minimizes the layout height by only shaping the soft blocks in the design. Iteratively, SDS shapes some soft blocks to minimize the layout height, with the guarantee that the layout width would not exceed the given upper bound. Rather than using some simple heuristic as in previous work, the amount of change on each block is determined by systematically distributing the global total amount of available slack to individual block. During the whole shaping process, the layout height is monotonically reducing, and eventually converges to an optimal solution. We also propose two optimality conditions to check the optimality of a shaping solution. To validate the efficiency and effectiveness of SDS, comprehensive experiments are conducted on MCNC and HB benchmarks. Compared with previous work, SDS is able to achieve the best experimental result with significantly faster runtime.

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Optimal floorplan area optimization

Cited by 67 publications

References 7 publications

Optimal cutting directions and rectangle orientation algorithm

Optimal cutting directions and rectangle orientation algorithm

SDS: An Optimal Slack-Driven Block Shaping Algorithm for Fixed-Outline Floorplanning

Optimal slack-driven block shaping algorithm in fixed-outline floorplanning

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