Fast layout processing methodologies for scalable distributed computing applications

Abstract

As the feature size shrinks to sub-20nm, more advanced OPC technologies such as ILT and the new lithographic resolution by EUV become the key solutions for device fabrication. These technologies leads to the file size explosion of up to hundreds of gigabytes of GDSII and OASIS files mainly due to the addition of complicated scattering bars and flattening of the design to compensate for long range effects. Splitting and merging layout files have been done sequentially in typical distributed computing layout applications. This portion becomes the bottle neck, causing the scalability to become poor. According to the Amdahl's law, minimizing the portion of sequential part is the key to get the maximum speed up. In this paper, we present scalable layout dividing and merging methodologies: Skeleton file based querying and direct OASIS file merging. These methods not only use a very minimum memory footprint but also achieve remarkable speed improvement. The skeleton file concept is very novel for a distributed application requiring geometrical processing, as it allows almost pseudo-random access into the input GDSII or OASIS file. Client machines can make use of the random access and perform fast query operations. The skeleton concept also works very well for flat input layouts, which is often the case of post-OPC data. Also, our OASIS file merging scheme is a smart approach which is equivalent of a binary file concatenation scheme. The merging method for OASIS files concatenates shape information in binary format with basic interpretation of bits with very low memory usage. We have observed that the skeleton file concept achieved 13.5 times speed improvement and used only 3.78% of memory on the master, over the conventional concept of converting into an internal format. Also, the merging speed is very fast, 28MB/sec and it is 44.5 times faster than conventional method. On top of the fast merging speed, it is very scalable since the merging time grows in linear fashion with respect to the file size. Our experiment setup includes hundreds of gigabytes of GDSII and OASIS files. We demonstrate in the paper, that the skeleton file based querying and direct OASIS file-merging schemes are very scalable for distributed computing applications for large volume layout. Additionally, we used embedded skeleton file scheme to improve file loading speed in layout viewer system and achieved 61 time speedup. We used Nirmaan, SoftJin's post-layout EDA toolkit for skeleton file based querying, OASIS file-merging and embedded skeleton file schemes.