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ABSTRACT

This paper presents a robust quadratic placement approach, which offers both high-quality placements and excellent computational efficiency. The additional force which distributes the modules on the chip in force-directed quadratic placement is separated into two forces: hold force and move force. Both of these forces are determined without any heuristics. Based on this novel systematic force implementation, we show that our iterative placement algorithm converges to an overlapfree placement. In addition, engineering change order (ECO) is efficiently supported by our placer. To handle the important trade-off between CPU time and placement quality, a deterministic quality control is presented.

In addition, a new linear net model is proposed, which accurately models the half-perimeter wirelength (HPWL) in the quadratic cost function of quadratic placement. HPWL in general is a linear metric for netlength and represents an efficient and common estimation for routed wirelength. Compared with the classical clique net model, our linear net model reduces memory usage by 75%, CPU time by 23% and netlength by 8%, which is measured by the HPWL of all nets.

Using the ISPD-2005 benchmark suite for comparison, our placer combined with the new linear net model has just 5.9% higher netlength but is 16x faster than APlace, which offers the best netlength in this benchmark. Compared to Capo, our placer has 9.2% lower netlength and is 5.4x faster.

In the recent ISPD-2006 placement contest, in which quality is mainly determined by netlength and CPU time, our placer together with the new net model produced excellent results.

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INDEX TERMS

Primary Classification:
  B. Hardware
  B.7 INTEGRATED CIRCUITS
      B.7.2 Design Aids
          Subjects: Placement and routing

Additional Classification:
  B. Hardware
  B.6 LOGIC DESIGN
      B.6.3 Design Aids
          Subjects: Optimization
  B.8 Performance and Reliability
      B.8.2 Performance Analysis and Design Aids

  G. Mathematics of Computing
  G.1 NUMERICAL ANALYSIS
      G.1.6 Optimization
          Subjects: Quadratic programming methods

General Terms:
Algorithms, Design, Performance