A maskless lithography system can replace expensive masks with a reusable, electronic mask. The maskless system requires extremely high throughput, around 10 Tbps, to match the wafer write speed of conventional lithography. We are focusing research on advanced data decompression techniques and a high-speed analog interface to the mask-writing mechanism.
Previous research has shown that Lempel-Ziv and Burrows-Wheeler can compress layout data well. We analyzed these algorithms for their suitability to hardware decompression. Lempel-Ziv is a pattern matching encoder followed by a Huffman encoder. Burrows-Wheeler is block sort followed by a locally-adaptive compression algorithm. Both of these algorithms are limited by memory available in compression and decompression—history buffer size for LZ and block size for BW. We found that we could stretch the effectiveness of limited memory in both algorithms by precompressing with a simple runlength-encode (RLE). RLE fares well because layout data typically has homogenous blocks. When sufficient memory is available, RLE has little effect on the compression ratio. But for memory-limited compression, RLE significantly improves the compression ratio. Burrows-Wheeler requires more memory to achieve the same compression ratio as Lempel-Ziv. BW also requires a more complex decompression architecture. Thus, we determined that RLE followed by LZ is best suited for hardware decompression of layout data.