Future lithography systems must produce more dense microchips with smaller feature sizes, while maintaining throughput comparable to today's optical lithography systems. This places stringent data-handling requirements on the design of any maskless lithography system. Today's optical lithography systems transfer one layer of data from the mask to the entire wafer in about sixty seconds. To achieve a similar throughput for a direct-write maskless lithography system with a pixel size of 22 nm, data rates of about 12 Tb/s are required. In this thesis, we propose a datapath architecture for delivering such a data rate to a parallel array of writers. Our proposed system achieves this data rate contingent on two assumptions: consistent 10 to 1 compression of lithography data, and implenieutstion of real-time hardwire decoder, compression of lithography data, and implementation of real-time hardware decoder, fabricated on a microchip together with a massively parallel array of lithography writers, capable of decoding 12 Tb/s of data. To address the compression efficiency problem, we explore a number of existing binary and gray-pixel lossless compression algorithms and apply them to a variety of microchip layers of typical circuits such as memory and control. The spectrum of algorithms include industry standard image compression algorithms such as JBIG and JPEG-LS, a wavelet based technique SPIHT, general file compression techniques ZIP and BZIP2, and a simple list-of-rectangles representation RECT. In addition, we develop a new technique, Context Copy Combinatorial Coding (C4), designed specifically for microchip layer images, with a low-complexity decoder for application to the datapath architecture. C4 combines the advantages of JBIG and ZIP, to achieve compression ratios higher than existing techniques. We have also devised Block C4, a variation of C4 with up to hundred times faster encoding times, with little or no loss in compression efficiency. The compression efficiency of various compression algorithms have been characterized on a variety of layouts sampled from many industry sources. In particular, the compression efficiency of Block C4, BZIP2, and ZIP is characterized for the Poly, Active, Contact, Metal1, Via1, and Metal2 layers of a complete industry 65 nm layout. Overall, we have found that compression efficiency varies significantly from design to design, from layer to layer, and even within parts of the same layer. It is difficult, if not impossible, to guarantee a lossless 10 to 1 compression for all lithography data, as desired in the design of our datapath architecture. Nonetheless, on the most complex Metall layer of our 65 nm full chip microprocessor design, we show that a average lossless compression of 5.2 is attainable, which corresponds to a throughput of 60 wafer layers per hour for a 0.77 Tb/s board-to-chip communications link. As a reference, state-of-the-art HyperTransport 3.0 offers 0.32 Tb/s per link. These numbers demonstrate the role lossless compression can play in the design of a maskless lithography datapath. The decoder for any chosen compression scheme must be replicated in hardware tens of thousands of times, to achieve the 12 Tb/s decoding rate. As such, decoder implementation complexity is a significant concern. We explore the tradeoff between the compression ratio, and decoder buffer size for C4, which constitutes a significant portion of the decoder implementation complexity. We show that for a fixed buffer size, C4 achieves a significantly higher compression ratio than those of existing compression algorithms. We also present a detailed functional block diagram of the C4 decoding algorithm as...