Paper
11 May 2009 Multi-core advantages for mask data preparation
Johnny Yeap, John Nogatch
Author Affiliations +
Abstract
Smaller design pattern feature sizes continue to increase mask data file sizes, which increases mask data processing (MDP) times. To satisfy the need for faster turn-around-time, MDP has progressively migrated from single-computer computation, to multi-threading, and then to distributed processing on multiple computers. The availability of low cost multi-core processors can be used advantageously to reduce Mask Data Preparation runtime. Compared to single core processors, multi-core processor have higher performance, however, total available memory and I/O bandwidth need to be increased proportionally with the additional cores. Memory per core and available I/O bandwidth limit the maximum number of cores that can be effective with distributed processing. When a single job is broken down to 2 or more tasks, the granularity of the tasks influences the efficiency of the processing. Smaller tasks allow for smaller memory footprint, better distribution of tasks and increased scalability, but increase input file access time and reduce output data compaction. By choosing a combination of multi-threading and distributed processing, faster run-time and better scalability can be achieved, as compared to either technique alone. The optimal configuration depends on the number of cores per processor, number of processors and memory per core.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Johnny Yeap and John Nogatch "Multi-core advantages for mask data preparation", Proc. SPIE 7379, Photomask and Next-Generation Lithography Mask Technology XVI, 73790Y (11 May 2009); https://doi.org/10.1117/12.824275
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Cited by 1 scholarly publication.
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KEYWORDS
Photomasks

Computing systems

Parallel processing

Received signal strength

Data processing

Information technology

Optical proximity correction

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