Study On Layout Transformation Algorithm

With the development of semiconductor industry, very large scale integration circuit(VLSIC) arises at the historic moment with the development of nanotechnology. At the moment of component towards miniaturization and circuit scale towards integration, layout optimization is becoming increasingly important as the link between layout design and the processes. Since most nets of CIF layout and the real defect outlines in the manufacturing process are irregular shaped in the actual layout optimization, layout optimization of random defects with the aid of image layout will be more effective, so the extraction of image layout from CIF layout becomes one choice to solve the problem of layout optimization. First, layout information is extracted into image file form CIF file. Then, the image is optimized with the help of image processing technology. Finally, the optimized image is transformed to the CIF file. The study on the transformation between CIF file and image is presented in the thesis.For the transformation from CIF to image, a method is proposed in this thesis which is based on the bit padding. Firstly a large “drawing board” is designed. Secondly, the statements in the CIF file are processed and “drawn” on the “board” one by one. Lastly, when the whole CIF is processed, the “drawing board” is separated into many small parts and every part is exported into one image. All this images lay a strong foundation for the further layout optimization. Compared with the existing extraction algorithm, this algorithm can solve the problem of complete extraction from larger CIF layout and has the advantages of accurate parameters, transparent extraction processes and small amount of background calculation.For the transformation from image to CIF, a method using the strategy of the edge detection is put forward in this thesis. According to the difference between the different shapes, shape information in the image is detected and translated into the corresponding CIF statement. To begin with, image edges are recognized and recorded in the form of chain code and this course is called boundary chain code tracking. In the meantime, using the run-length encoding instead of chain code can improve the storage efficiency. In addition, according to the characteristic of chain code, the specific shape that chain code describes can be determined. Last, in accordance with the rules of CIF statement,calculate the results. As to the complex image which has holes, there is a feasible method solving the disappearance of the holes in the thesis.The method presented in this thesis has the advantages of popularity and high efficiency. It not only suitable for complex layout, but also avoid lots of reduplicative calculation. It does not have the procedure of choosing effective data before processing so as to reduce the time of invalid data processing. The results on experimental layouts show that the new extraction algorithm and transformation method not only has the higher efficiency on large scale CIF layout but also has the advantages of higher stability and good portability.