Comparison of OPC job prioritization schemes to generate data for mask manufacturing

Travis Lewis; Vijay Veeraraghavan; Kenneth Jantzen; Stephen Kim; Minyoung Park; Gordon Russell; Mark Simmons

doi:10.1117/12.2086927

18 March 2015 Comparison of OPC job prioritization schemes to generate data for mask manufacturing

Travis Lewis, Vijay Veeraraghavan, Kenneth Jantzen, Stephen Kim, Minyoung Park, Gordon Russell, Mark Simmons

Proceedings Volume 9427, Design-Process-Technology Co-optimization for Manufacturability IX; 942711 (2015) https://doi.org/10.1117/12.2086927
Event: SPIE Advanced Lithography, 2015, San Jose, California, United States

Abstract

Delivering mask ready OPC corrected data to the mask shop on-time is critical for a foundry to meet the cycle time commitment for a new product. With current OPC compute resource sharing technology, different job scheduling algorithms are possible, such as, priority based resource allocation and fair share resource allocation. In order to maximize computer cluster efficiency, minimize the cost of the data processing and deliver data on schedule, the trade-offs of each scheduling algorithm need to be understood. Using actual production jobs, each of the scheduling algorithms will be tested in a production tape-out environment. Each scheduling algorithm will be judged on its ability to deliver data on schedule and the trade-offs associated with each method will be analyzed. It is now possible to introduce advance scheduling algorithms to the OPC data processing environment to meet the goals of on-time delivery of mask ready OPC data while maximizing efficiency and reducing cost.

Citation Download Citation

Travis Lewis, Vijay Veeraraghavan, Kenneth Jantzen, Stephen Kim, Minyoung Park, Gordon Russell, and Mark Simmons "Comparison of OPC job prioritization schemes to generate data for mask manufacturing", Proc. SPIE 9427, Design-Process-Technology Co-optimization for Manufacturability IX, 942711 (18 March 2015); https://doi.org/10.1117/12.2086927

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