Mask Data Preparation (MDP), which typically consists of Boolean operations, sizing, mask rule check (MRC) and
fracturing, requires intense computing power. For today's increasingly large data, utilizing distributed parallel processing
with multiple CPUs or using a host server is an established approach to reduce turn around time (TAT). A data analysis
and distributing loads are usually required in its preparation process, however it is inevitably a sequential process by its
nature, which severely affects the overall TAT. An inappropriate preparation process causes uneven loads for the parallel
processing and leads to an increase of TAT. It is challenging especially when a large number of parallel processing nodes
are used. This paper introduces a novel methodology of an efficient parallel processing to run an MDP. The involving
tests and analysis have been applied to layout data formats by using MaskStudio version 6 (MS6) fracturing system.
MS6 takes the method of grid-based partitioning as the preparing process of parallel processing, and each partition is
processed for such as Boolean operation, sizing and MRC. By increasing parallel processing nodes, this methodology
successfully showed the reduction of the process time.