Transform-Based Lossless Image Compression Algorithm for Electron Beam Direct Write Lithography Systems

Abstract

Conventional photolithography systems use physical masks which are expensive and difficult to create and cannot be used forever. Electron BeamDirectWrite (EBDW) lithography systems are a noteworthy alternative which do not need physical masks [Chokshi et al. (1999)]. As shown in Figure 1 they rely on an array of lithography writers to directly write a mask image on a photo-resist coated wafer using electron beams. EBDW systems are attractive for a few reasons: First, their flexibility is advantageous in processes requiring the rapid prototyping of chips. Second, they are known to reduce fabrication costs [Lin (2009)]. Third, they are well suited for Next-Generation Lithography (NGL) because they are able to produce circuits with smaller features than state-of-the-art photolithography systems. Finally, since the mask images are electronically controlled EBDW systems could be improved by software. Our focus here will be on this last point. EBDW is not at this time used in many circuit fabrication processes because it is much slower than physical mask lithography systems. One current focus of research to address the throughput problem is massively-parallel electron beam lithography. Some of the research groups/companies which are developing such systems include KLA-Tencor [Petric et al. (2009)], IMS [Klein et al. (2009)], and MAPPER [Wieland et al. (2009)]. Chokshi et al. (1999) proposed a maskless lithography system using a bank of 80,000 lithography writers running in parallel at 24 MHz. Dai & Zakhor (2006) pointed out that this lithography system can achieve the conventional photolithography throughput of one wafer layer per minute, but layout image data is often several hundred terabits per wafer and therefore data delivery becomes an important issue. Dai & Zakhor (2006) proposed using a data delivery system with a lossless image compression component which is illustrated in Figure 2. They hold compressed layout images in storage disks and transmit the compressed data to the processor memory board. This kind of EBDW lithography system can achieve higher throughput if the decoder embedded within the lithography writer can sufficiently rapidly recover the original images from the compressed files. Dai (2008) discussed two constraints on this type of system: 1) the compression ratio should be at least (Transfer rate of Decoder to Writer / Transfer rate of Memory to Decoder), and 2) the decoding algorithm has to be simple enough to be implemented as a small add-on within the maskless lithography writer. Therefore the decoder must operate with little memory. Transform-Based Lossless Image Compression Algorithm for Electron Beam Direct Write Lithography Systems