Multi-Core Advantages for Mask Data Preparation

摘要

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.