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GDSII is a data format of the circuit design file for producing semiconductor. GDSII is also used as a transfer format for fabricating photo mask as well. As design rules are getting smaller and RET (Resolution Enhancement Technology) is getting more complicated, the time of converting GDSII to a mask data format has been increased, which influences the period of mask production. Photo mask shops all over the world are widely using computer clusters which are connected through a network, that is, called distributed computing method, to reduce the converting time. Commonly computing resource for conversion is assigned based on the input file size. However, the result of experiments showed that the input file size was improper to predict the computing resource usage. In this paper, we propose the methodology of artificial intelligence with considering the properties of GDSII file to handle circuit design files more efficiently. The conversion time will be optimized by controlling the hardware resource for data conversion as long as the conversion time is predictable through analyzing the design data. Neural networks are used to predict the conversion time for this research. In this paper, the application of neural networks for the time prediction will be discussed and experimental results will be shown with comparing to statistical model based approaches.

As the critical dimension (CD) becomes smaller, various resolution enhancement techniques (RET) are widely adopted. In developing sub-100nm devices, the complexity of optical proximity correction (OPC) is severely increased and applied OPC layers are expanded to non-critical layers. The transformation of designed pattern data by OPC operation causes complexity, which cause runtime overheads to following steps such as mask data preparation (MDP), and collapse of existing design hierarchy. Therefore, many mask shops exploit the distributed computing method in order to reduce the runtime of mask data preparation rather than exploit the design hierarchy. Distributed computing uses a cluster of computers that are connected to local network system. However, there are two things to limit the benefit of the distributing computing method in MDP. First, every sequential MDP job, which uses maximum number of available CPUs, is not efficient compared to parallel MDP job execution due to the input data characteristics. Second, the runtime enhancement over input cost is not sufficient enough since the scalability of fracturing tools is limited. In this paper, we will discuss optimum load balancing environment that is useful in increasing the uptime of distributed computing system by assigning appropriate number of CPUs for each input design data. We will also describe the distributed processing (DP) parameter optimization to obtain maximum throughput in MDP job processing.

In this paper, the influence of dose modulation on CD trend by using electron beam exposure model has beeninvestigated and simulated. To predict CD trend, we developed an analysis program, which shows theexposed energy profile and the corrected CD distribution in mask. First, it calculates the factor of foggingeffect correction (D1) from pattern density distribution with the assumption that fogging effect depends on onlypattern density. And then it calculates the modified dose for correcting both proximity and fogging effect.From dose distribution, the corrected CD is calculated analytically by using e-beam lithography model: seeFigure 1 . It can give a glance how the dose modulation method has an influence on the CD uniformity.Moreover, the result of global error correction such as side, radial error at the mask writing stage has beenanalyzed in this study.Keywords: Fogging effect, Proximity effect correction, Dose modulation, Variable shaped beam 1. INTRODUCTION As the minimum feature size approaches the resolution limit of optical lithography, mask critical dimension(CD) error becomes one of the main sources to determine a device quality. To achieve critical dimensionaccuracy and higher resolution in mask writing, 5OKeV variable shaped beam (VSB) system is widely used inmask fabrication. However, as a high acceleration voltage system is adapted, fogging effect (caused by re-scattering electrons) affects global CD trend on mask. In order to compensate global CD trend affected byfogging effect, dose modulation method that used for performing proximity effect correction (PEC) is appliedduring the e-beam lithographic processes. Namely, it modulates the exposure dose for correcting bothproximity and fogging effect. Calculated dose (D) can be described as, D =