Share Email Print

Proceedings Paper

Lossless compression techniques for maskless lithography data
Author(s): Vito Dai; Avideh Zakhor
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Future lithography systems must produce more dense chips with smaller feature sizes, while maintaining the throughput of one wafer per sixty seconds per layer achieved by today's optical lithography systems. To achieve this throughput with a direct-write maskless lithography system, using 25 nm pixels for 50 nm feature sizes, requires data rates of about 10 Tb/s. In a previous paper, we presented an architecture which achieves this data rate contingent on consistent 25 to 1 compression of lithography data, and on implementation of a decoder-writer chip with a real-time decompressor fabricated on the same chip as the massively parallel array of lithography writers. In this paper, we examine the compression efficiency of a spectrum of techniques suitable for lithography data, including two industry standards JBIG and JPEG-LS, a wavelet based technique SPIHT, general file compression techniques ZIP and BZIP2, our own 2D-LZ technique, and a simple list-of-rectangles representation RECT. Layouts rasterized both to black-and-white pixels, and to 32 level gray pixels are considered. Based on compression efficiency, JBIG, ZIP, 2D-LZ, and BZIP2 are found to be strong candidates for application to maskless lithography data, in many cases far exceeding the required compression ratio of 25. To demonstrate the feasibility of implementing the decoder-writer chip, we consider the design of a hardware decoder based on ZIP, the simplest of the four candidate techniques. The basic algorithm behind ZIP compression is Lempel-Ziv 1977 (LZ77), and the design parameters of LZ77 decompression are optimized to minimize circuit usage while maintaining compression efficiency.

Paper Details

Date Published: 1 July 2002
PDF: 12 pages
Proc. SPIE 4688, Emerging Lithographic Technologies VI, (1 July 2002); doi: 10.1117/12.472334
Show Author Affiliations
Vito Dai, Univ. of California/Berkeley (United States)
Avideh Zakhor, Univ. of California/Berkeley (United States)

Published in SPIE Proceedings Vol. 4688:
Emerging Lithographic Technologies VI
Roxann L. Engelstad, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?