JOURNAL ARTICLE

Reduced complexity compression algorithms for direct-write maskless lithography systems

Hsin-I LiuVito DaiAvideh ZakhorBorivoje Nikolić

Year: 2006 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 6151 Pages: 61512B-61512B   Publisher: SPIE

Abstract

Achieving the throughput of one wafer layer per minute with a direct-write maskless lithography system, using 22 nm pixels for 45 nm feature sizes, requires data rates of about 12 Tb/s. In our previous work, we developed a novel lossless compression technique specifically tailored to flattened, rasterized, layout data called Context-Copy-Combinatorial-Code (C4) which exceeds the compression efficiency of all other existing techniques including BZIP2, 2D-LZ, and LZ77, especially under limited decoder buffer size, as required for hardware implementation. In this paper, we present two variations of the C4 algorithm. The first variation, Block C4, lowers the encoding time of C4 by several orders of magnitude, concurrently with lowering the decoder complexity. The second variation which involves replacing hierarchical combinatorial coding part of C4 with Golomb run-length coding, significantly reduces the decoder power and area as compared to Block C4. We refer to this algorithm as Block Golomb Context Copy Code (Block GC3). We present the detailed functional block diagrams of Block C4 and Block GC3 decoders along with their hardware performance estimates as the first step of implementing the writer chip for maskless lithography.

Keywords:
Computer science Algorithm Lossless compression Block (permutation group theory) Data compression Context (archaeology) Decoding methods Golomb coding Lithography Computer hardware Image compression Image processing Artificial intelligence Optics

Metrics

14
Cited By
1.34
FWCI (Field Weighted Citation Impact)
0
Refs
0.82
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advancements in Photolithography Techniques
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Advanced Data Storage Technologies
Physical Sciences →  Computer Science →  Computer Networks and Communications
Algorithms and Data Compression
Physical Sciences →  Computer Science →  Artificial Intelligence

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