A bit-serial computing accelerator for solving 2D/3D laplace and poisson equations
Partial differential equations (PDEs) play a pivotal role in various scientific and engineering fields due to their capability to model and solve numerous real-world problems. For edge devices, the need for low-power consumption and real-time processing is crucial. This thesis proposes a bit-serial...
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Nanyang Technological University
2025
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sg-ntu-dr.10356-1821792025-01-14T05:37:01Z A bit-serial computing accelerator for solving 2D/3D laplace and poisson equations Liu, Sicheng Zheng Yuanjin School of Electrical and Electronic Engineering YJZHENG@ntu.edu.sg Engineering Bit-serial computing Partial differential equations Partial differential equations (PDEs) play a pivotal role in various scientific and engineering fields due to their capability to model and solve numerous real-world problems. For edge devices, the need for low-power consumption and real-time processing is crucial. This thesis proposes a bit-serial computing accelerator, accompanied by simulation results, that demonstrates a compact chip area, low power consumption, and high computational efficiency. Furthermore, several optimization techniques have been integrated to enhance performance. Potential future research directions are also discussed, including memory compression strategies and the integration of physics-informed neural networks (PINNs). Master's degree 2025-01-14T05:36:29Z 2025-01-14T05:36:29Z 2024 Thesis-Master by Coursework Liu, S. (2024). A bit-serial computing accelerator for solving 2D/3D laplace and poisson equations. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/182179 https://hdl.handle.net/10356/182179 en application/pdf Nanyang Technological University |
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Engineering Bit-serial computing Partial differential equations |
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Engineering Bit-serial computing Partial differential equations Liu, Sicheng A bit-serial computing accelerator for solving 2D/3D laplace and poisson equations |
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Partial differential equations (PDEs) play a pivotal role in various scientific and engineering fields due to their capability to model and solve numerous real-world problems. For edge devices, the need for low-power consumption and real-time processing is crucial. This thesis proposes a bit-serial computing accelerator, accompanied by simulation results, that demonstrates a compact chip area, low power consumption, and high computational efficiency. Furthermore, several optimization techniques have been integrated to enhance performance. Potential future research directions are also discussed, including memory compression strategies and the integration of physics-informed neural networks (PINNs). |
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Zheng Yuanjin |
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Zheng Yuanjin Liu, Sicheng |
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Thesis-Master by Coursework |
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Liu, Sicheng |
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Liu, Sicheng |
title |
A bit-serial computing accelerator for solving 2D/3D laplace and poisson equations |
title_short |
A bit-serial computing accelerator for solving 2D/3D laplace and poisson equations |
title_full |
A bit-serial computing accelerator for solving 2D/3D laplace and poisson equations |
title_fullStr |
A bit-serial computing accelerator for solving 2D/3D laplace and poisson equations |
title_full_unstemmed |
A bit-serial computing accelerator for solving 2D/3D laplace and poisson equations |
title_sort |
bit-serial computing accelerator for solving 2d/3d laplace and poisson equations |
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Nanyang Technological University |
publishDate |
2025 |
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https://hdl.handle.net/10356/182179 |
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1821279345179623424 |