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21 March 2012 Scalable simulations for directed self-assembly patterning with the use of GPU parallel computing
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Abstract
Directed self-assembly (DSA) patterning has been increasingly investigated as an alternative lithographic process for future technology nodes. One of the critical specs for DSA patterning is defects generated through annealing process or by roughness of pre-patterned structure. Due to their high sensitivity to the process and wafer conditions, however, characterization of those defects still remain challenging. DSA simulations can be a powerful tool to predict the formation of the DSA defects. In this work, we propose a new method to perform parallel computing of DSA Monte Carlo (MC) simulations. A consumer graphics card was used to access its hundreds of processing units for parallel computing. By partitioning the simulation system into non-interacting domains, we were able to run MC trial moves in parallel on multiple graphics-processing units (GPUs). Our results show a significant improvement in computational performance.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kenji Yoshimoto, Brandon L. Peters, Gurdaman S. Khaira, and Juan J. de Pablo "Scalable simulations for directed self-assembly patterning with the use of GPU parallel computing", Proc. SPIE 8323, Alternative Lithographic Technologies IV, 83232P (21 March 2012); https://doi.org/10.1117/12.917830
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