VoxCap: FFT-accelerated and Tucker-enhanced capacitance extraction simulator for voxelized structures
VoxCap, a fast Fourier transform (FFT)-accelerated and Tucker-enhanced integral equation simulator for capacitance extraction of voxelized structures, is proposed. The VoxCap solves the surface integral equations (SIEs) for conductor and dielectric surfaces with three key attributes that make the...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2022
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/159505 |
| _version_ | 1824454992779542528 |
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| author | Wang, Mingyu Qian, Cheng White, Jacob K. Yucel, Abdulkadir C. |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Wang, Mingyu Qian, Cheng White, Jacob K. Yucel, Abdulkadir C. |
| author_sort | Wang, Mingyu |
| collection | NTU |
| description | VoxCap, a fast Fourier transform (FFT)-accelerated and Tucker-enhanced
integral equation simulator for capacitance extraction of voxelized structures,
is proposed. The VoxCap solves the surface integral equations (SIEs) for
conductor and dielectric surfaces with three key attributes that make the
VoxCap highly CPU and memory efficient for the capacitance extraction of the
voxelized structures: (i) VoxCap exploits the FFTs for accelerating the
matrix-vector multiplications during the iterative solution of linear system of
equations arising due to the discretization of SIEs. (ii) During the iterative
solution, VoxCap uses a highly effective and memory-efficient preconditioner
that reduces the number of iterations significantly. (iii) VoxCap employs
Tucker decompositions to compress the block Toeplitz and circulant tensors,
requiring the largest memory in the simulator. By doing so, it reduces the
memory requirement of these tensors from hundreds of gigabytes to a few
megabytes and the CPU time required to obtain Toeplitz tensors from tens of
minutes (even hours) to a few seconds for very large scale problems. VoxCap is
capable of accurately computing capacitance of arbitrarily shaped and
large-scale voxelized structures on a desktop computer. |
| first_indexed | 2025-02-19T03:31:08Z |
| format | Journal Article |
| id | ntu-10356/159505 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2025-02-19T03:31:08Z |
| publishDate | 2022 |
| record_format | dspace |
| spelling | ntu-10356/1595052022-06-24T05:52:17Z VoxCap: FFT-accelerated and Tucker-enhanced capacitance extraction simulator for voxelized structures Wang, Mingyu Qian, Cheng White, Jacob K. Yucel, Abdulkadir C. School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Capacitance Extraction Electrostatic Analysis VoxCap, a fast Fourier transform (FFT)-accelerated and Tucker-enhanced integral equation simulator for capacitance extraction of voxelized structures, is proposed. The VoxCap solves the surface integral equations (SIEs) for conductor and dielectric surfaces with three key attributes that make the VoxCap highly CPU and memory efficient for the capacitance extraction of the voxelized structures: (i) VoxCap exploits the FFTs for accelerating the matrix-vector multiplications during the iterative solution of linear system of equations arising due to the discretization of SIEs. (ii) During the iterative solution, VoxCap uses a highly effective and memory-efficient preconditioner that reduces the number of iterations significantly. (iii) VoxCap employs Tucker decompositions to compress the block Toeplitz and circulant tensors, requiring the largest memory in the simulator. By doing so, it reduces the memory requirement of these tensors from hundreds of gigabytes to a few megabytes and the CPU time required to obtain Toeplitz tensors from tens of minutes (even hours) to a few seconds for very large scale problems. VoxCap is capable of accurately computing capacitance of arbitrarily shaped and large-scale voxelized structures on a desktop computer. Ministry of Education (MOE) Nanyang Technological University This work was supported by the Ministry of Education, Singapore, under Grant AcRF TIER 1-2018-T1-002-077 (RG 176/18), and in part by Nanyang Technological University under a startup grant. 2022-06-24T05:52:17Z 2022-06-24T05:52:17Z 2020 Journal Article Wang, M., Qian, C., White, J. K. & Yucel, A. C. (2020). VoxCap: FFT-accelerated and Tucker-enhanced capacitance extraction simulator for voxelized structures. IEEE Transactions On Microwave Theory and Techniques, 68(12), 5154-5168. https://dx.doi.org/10.1109/TMTT.2020.3022091 0018-9480 https://hdl.handle.net/10356/159505 10.1109/TMTT.2020.3022091 2-s2.0-85097795885 12 68 5154 5168 en 2018-T1-002-077 (RG 176/18) IEEE Transactions on Microwave Theory and Techniques © 2020 IEEE. All rights reserved. |
| spellingShingle | Engineering::Electrical and electronic engineering Capacitance Extraction Electrostatic Analysis Wang, Mingyu Qian, Cheng White, Jacob K. Yucel, Abdulkadir C. VoxCap: FFT-accelerated and Tucker-enhanced capacitance extraction simulator for voxelized structures |
| title | VoxCap: FFT-accelerated and Tucker-enhanced capacitance extraction simulator for voxelized structures |
| title_full | VoxCap: FFT-accelerated and Tucker-enhanced capacitance extraction simulator for voxelized structures |
| title_fullStr | VoxCap: FFT-accelerated and Tucker-enhanced capacitance extraction simulator for voxelized structures |
| title_full_unstemmed | VoxCap: FFT-accelerated and Tucker-enhanced capacitance extraction simulator for voxelized structures |
| title_short | VoxCap: FFT-accelerated and Tucker-enhanced capacitance extraction simulator for voxelized structures |
| title_sort | voxcap fft accelerated and tucker enhanced capacitance extraction simulator for voxelized structures |
| topic | Engineering::Electrical and electronic engineering Capacitance Extraction Electrostatic Analysis |
| url | https://hdl.handle.net/10356/159505 |
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