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Implementation and evaluation of the Level Set method: Towards efficient and accurate simulation of wet etching for microengineering applications.

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Title: Implementation and evaluation of the Level Set method: Towards efficient and accurate simulation of wet etching for microengineering applications.
Authors: Montoliu, C.1 carmonal@upv.es, Ferrando, N.2,3, Gosálvez, M.A.3,4, Cerdá, J.1, Colom, R.J.1
Source: Computer Physics Communications. Oct2013, Vol. 184 Issue 10, p2299-2309. 11p.
Subjects: Level set methods, Simulation methods & models, Etching, Electromechanical devices, Graphics processing units, Computational complexity
Abstract: Abstract: The use of atomistic methods, such as the Continuous Cellular Automaton (CCA), is currently regarded as a computationally efficient and experimentally accurate approach for the simulation of anisotropic etching of various substrates in the manufacture of Micro-electro-mechanical Systems (MEMS). However, when the features of the chemical process are modified, a time-consuming calibration process needs to be used to transform the new macroscopic etch rates into a corresponding set of atomistic rates. Furthermore, changing the substrate requires a labor-intensive effort to reclassify most atomistic neighborhoods. In this context, the Level Set (LS) method provides an alternative approach where the macroscopic forces affecting the front evolution are directly applied at the discrete level, thus avoiding the need for reclassification and/or calibration. Correspondingly, we present a fully-operational Sparse Field Method (SFM) implementation of the LS approach, discussing in detail the algorithm and providing a thorough characterization of the computational cost and simulation accuracy, including a comparison to the performance by the most recent CCA model. We conclude that the SFM implementation achieves similar accuracy as the CCA method with less fluctuations in the etch front and requiring roughly 4 times less memory. Although SFM can be up to 2 times slower than CCA for the simulation of anisotropic etchants, it can also be up to 10 times faster than CCA for isotropic etchants. In addition, we present a parallel, GPU-based implementation (gSFM) and compare it to an optimized, multicore CPU version (cSFM), demonstrating that the SFM algorithm can be successfully parallelized and the simulation times consequently reduced, while keeping the accuracy of the simulations. Although modern multicore CPUs provide an acceptable option, the massively parallel architecture of modern GPUs is more suitable, as reflected by computational times for gSFM up to 7.4 times faster than for cSFM. [Copyright &y& Elsevier]
Copyright of Computer Physics Communications is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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DbLabel: Engineering Source
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  Data: Implementation and evaluation of the Level Set method: Towards efficient and accurate simulation of wet etching for microengineering applications.
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  Data: <searchLink fieldCode="AR" term="%22Montoliu%2C+C%2E%22">Montoliu, C.</searchLink><relatesTo>1</relatesTo><i> carmonal@upv.es</i><br /><searchLink fieldCode="AR" term="%22Ferrando%2C+N%2E%22">Ferrando, N.</searchLink><relatesTo>2,3</relatesTo><br /><searchLink fieldCode="AR" term="%22Gosálvez%2C+M%2EA%2E%22">Gosálvez, M.A.</searchLink><relatesTo>3,4</relatesTo><br /><searchLink fieldCode="AR" term="%22Cerdá%2C+J%2E%22">Cerdá, J.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Colom%2C+R%2EJ%2E%22">Colom, R.J.</searchLink><relatesTo>1</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Computer+Physics+Communications%22">Computer Physics Communications</searchLink>. Oct2013, Vol. 184 Issue 10, p2299-2309. 11p.
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  Data: <searchLink fieldCode="DE" term="%22Level+set+methods%22">Level set methods</searchLink><br /><searchLink fieldCode="DE" term="%22Simulation+methods+%26+models%22">Simulation methods & models</searchLink><br /><searchLink fieldCode="DE" term="%22Etching%22">Etching</searchLink><br /><searchLink fieldCode="DE" term="%22Electromechanical+devices%22">Electromechanical devices</searchLink><br /><searchLink fieldCode="DE" term="%22Graphics+processing+units%22">Graphics processing units</searchLink><br /><searchLink fieldCode="DE" term="%22Computational+complexity%22">Computational complexity</searchLink>
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  Data: Abstract: The use of atomistic methods, such as the Continuous Cellular Automaton (CCA), is currently regarded as a computationally efficient and experimentally accurate approach for the simulation of anisotropic etching of various substrates in the manufacture of Micro-electro-mechanical Systems (MEMS). However, when the features of the chemical process are modified, a time-consuming calibration process needs to be used to transform the new macroscopic etch rates into a corresponding set of atomistic rates. Furthermore, changing the substrate requires a labor-intensive effort to reclassify most atomistic neighborhoods. In this context, the Level Set (LS) method provides an alternative approach where the macroscopic forces affecting the front evolution are directly applied at the discrete level, thus avoiding the need for reclassification and/or calibration. Correspondingly, we present a fully-operational Sparse Field Method (SFM) implementation of the LS approach, discussing in detail the algorithm and providing a thorough characterization of the computational cost and simulation accuracy, including a comparison to the performance by the most recent CCA model. We conclude that the SFM implementation achieves similar accuracy as the CCA method with less fluctuations in the etch front and requiring roughly 4 times less memory. Although SFM can be up to 2 times slower than CCA for the simulation of anisotropic etchants, it can also be up to 10 times faster than CCA for isotropic etchants. In addition, we present a parallel, GPU-based implementation (gSFM) and compare it to an optimized, multicore CPU version (cSFM), demonstrating that the SFM algorithm can be successfully parallelized and the simulation times consequently reduced, while keeping the accuracy of the simulations. Although modern multicore CPUs provide an acceptable option, the massively parallel architecture of modern GPUs is more suitable, as reflected by computational times for gSFM up to 7.4 times faster than for cSFM. [Copyright &y& Elsevier]
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  Data: <i>Copyright of Computer Physics Communications is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1016/j.cpc.2013.05.016
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        Text: English
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      – SubjectFull: Etching
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      – SubjectFull: Graphics processing units
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      – SubjectFull: Computational complexity
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      – TitleFull: Implementation and evaluation of the Level Set method: Towards efficient and accurate simulation of wet etching for microengineering applications.
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              Text: Oct2013
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