计算机科学
线性
吞吐量
光学
弹性(材料科学)
像素
错误检测和纠正
集合(抽象数据类型)
航程(航空)
算法
人工智能
电子工程
材料科学
物理
电信
复合材料
工程类
程序设计语言
无线
作者
Harold Zable,Hironobu Matsumoto,Kenichi Yasui,Ryosuke Ueba,Noriaki Nakayamada,Nagesh Shirali,Yukihiro Masuda,Ryan Pearman,Aki Fujimura
摘要
Over the last two decades, eBeam mask writers have added inline correction features. Particularly when minimum feature sizes on mask went below 100nm a decade ago, the need for more precision within a reasonable write time increased the demand for more corrections. Inline correction is better for turnaround time and throughput, but inline correction is computationally limited because it is unacceptable for computation to limit the machine write time. Simultaneously, the same need for linearity correction, printability enhancement, and resilience to manufacturing variation has caused much innovation in offline mask data preparation and mask process correction. Typically, the writer performs inline correction for backscatter, fogging, loading, charging and thermal effects, but leaves <10μm effects to offline correction. With multi-beam writers, the write time is independent of shape count. Any set of input shapes is rasterized to a set of arrays of equal sized pixels that are each independently dosed to write the desired shapes. Multi-beam writers also have a certain minimum write time that is required for writing even a very small number of simple shapes. This gives rise to the possibility of providing linearity correction features, even for the short-range effects as inline correction in the writer. Such inline correction has zero impact on throughput and turnaround time of mask making. This paper introduces the GPU-accelerated inline linearity correction capability of the NuFlare MBM-1000 for the first time.
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