An Effective Floorplanning Algorithm in Mixed Mode Placement Integrated with Rectilinear-Shaped Optimization for Soft Bl

1. An Effective Floorplanning Algorithm in Mixed Mode Placement Integrated with Rectilinear-Shaped Optimization for Soft Blocks Changqi Yang, Xianlong Hong, Hannah Yang EDA Lab, Tsinghua University Strategic CAD Labs, Intel Corporation

2. Content • Motivation • Outline of the Floorplan Algorithm RSF • Experimental Results • Summary

3. Motivation Mixed Mode Placement • Mixed Mode Placement (MMP) problem can be successfully solved by combining floorplanning and cell based placement according to circuit's hierarchy. • Partition • Floorplan • Placement

4. Motivation Floorplanning is the Key Stage in MMP • Floorplanning is the key phase during the whole design stages of MMP because the shorter wire length of floorplanning can reduce the final wire length after global / detailed placement. • Restricting virtual blocks’ shapes to be fixed or be rectangular will limit the quality of floorplanning.

5. Motivation Previous Works • Soften virtual blocks by changing their width and height • 2000, Ma, “VLSI floorplanning with Fixed Topology” • L/T shaped floorplanning • 2001, Ma, "Floorplanning with Abutment Constraints ..." • Grid-based floorplanning algorithm to optimize the shape of virtual blocks • 2000, Dinesh P. Mehta, "On the Use of Flexible, ..." • Lagrange Relaxation method to modify the shapes and dimensions of modules to fill up the unused area of a preliminary floorplanning • 2002, F.Y.Young, "Non-rectangular shaping and sizing ..."

6. Motivation Virtual Block • Virtual blocks are composed by standard cells. • Virtual blocks’ features: • They can expand their area • They can be transformed into rectilinear-shape. • They connect to other blocks through virtual pins.

7. Outline of Algorithm Main Flow

8. Outline of Algorithm RSO • MBB - Minimal Bounding Box • The half-perimeter of this bounding box is corresponding to the minimal wire length of the net in half-perimeter mode • MBBI – Minimal Bounding Box Intersection • The virtual pin can be allocated at the point of intersection between the MBB and the virtual block which the virtual pin belongs to • DSA – Dead Space Attachment • RSO can reduce the wire length if it can result in the smaller MBB of nets. It starts from searching DSB during the packing and then attaches the DSB to the virtual blocks properly.

9. Outline of Algorithm MBB & MBBI • The minimal wire length of a net is: • Draw a MMB according to the formula • MBB would retrogress to be a line • Find MBB with rectilinear-shaped block by enumerating all MBB candidates among sub blocks and selecting the one with minimal perimeter.

10. Outline of Algorithm Find the Dead Space • CBL is adopted as the representation of blocks’ topology. • In CBL, all the dead-space blocks can be found during the process of packing.

11. Outline of Algorithm DSA • Gain: • Potential Gain:

12. Outline of Algorithm DSA Algorithm • Algorithm DSA() • DS: the set of DSB in packing • { • construct DS during packing according to lemma 3; • for each D in DS do • for each attachment do • calculate G according to formula (2); • calculate G' according to formula (3); • end for • select an attachment A with maximal G; • if G(A)>0 then • complete this attachment; • else • select an attachment A with maximal G'; • if G'(A) > 0 then • complete this attachment; • end if • end if • end for • }

13. Name WireLen Min/Aver Virtual # 20% Virtual #50% Virtual #100% Min/Aver Impr (%) Min/Aver Impr (%) Min/Aver Impr (%) ami33 39.431/ 48.947 38.189/ 40.657 3.2/ 16.9 32.427/ 33.781 17.8/ 30.9 19.911/ 22.903 49.5/ 53.2 ami49 710.220/ 775.551 730.156/ 757.099 -2.8/ 2.4 667.203/ 689.463 6.1/ 11.1 444.975/ 480.984 37.3/ 37.9 apte 194.950/ 202.830 160.227/ 209.284 17.8/ -3.2 160.68/ 177.243 17.6/ 12.6 74.187/ 113.626 61.9/ 43.9 xerox 403.466/ 533.916 347.719/ 411.925 13.8/ 22.8 303.507/ 365.3 24.8/ 31.6 192.323/ 237.822 52.3/ 55.5 Experimental Results Results on MCNC Cases

14. Circuits #cells #macro blocks #nets Block area (average) /cell area(average) block2 7094 2 10049 2045 block6 5996 6 10049 872 block8 5662 8 10049 695 block9 5895 9 10049 751 block10 5151 10 10049 676 Experimental Results Results on MMP

15. Name HMMP WireLen MMP WireLen Impr(%) HMMP RTime(s) MMP RTime(s) block 2 1.692e6 1.608e6 5.0 358 320 block 6 2.029e6 1.435e6 29.3 382 335 block 8 2.022e6 1.409e6 30.3 405 314 block9 2.345e6 1.552e6 33.8 388 295 block 10 2.131e6 1.240e6 41.8 388 356 Experimental Results Results on MMP (2)

16. Summary Summary • The floorplanning algorithm integrated with rectilinear-shaped optimization is effective. • It can achieve good floorplanning quality when virtual blocks exist. • The MMP involving the algorithm as its floorplanning stage can obtain better performance in final placement results

17. Thank you!!!