Dataflow Optimized Reconfigurable Acceleration for FEM-based CFD Simulations
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| Main Authors: | , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866917978519371776 |
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| author | Kapetanakis, Anastassis Ferikoglou, Aggelos Anagnostopoulos, George Xydis, Sotirios |
| author_facet | Kapetanakis, Anastassis Ferikoglou, Aggelos Anagnostopoulos, George Xydis, Sotirios |
| contents | Computational Fluid Dynamics (CFD) simulations are essential for analyzing and optimizing fluid flows in a wide range of real-world applications. These simulations involve approximating the solutions of the Navier-Stokes differential equations using numerical methods, which are highly compute- and memory-intensive due to their need for high-precision iterations. In this work, we introduce a high-performance FPGA accelerator specifically designed for numerically solving the Navier-Stokes equations. We focus on the Finite Element Method (FEM) due to its ability to accurately model complex geometries and intricate setups typical of real-world applications. Our accelerator is implemented using High-Level Synthesis (HLS) on an AMD Alveo U200 FPGA, leveraging the reconfigurability of FPGAs to offer a flexible and adaptable solution. The proposed solution achieves 7.9x higher performance than optimized Vitis-HLS implementations and 45% lower latency with 3.64x less power compared to a software implementation on a high-end server CPU. This highlights the potential of our approach to solve Navier-Stokes equations more effectively, paving the way for tackling even more challenging CFD simulations in the future. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2411_16245 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Dataflow Optimized Reconfigurable Acceleration for FEM-based CFD Simulations Kapetanakis, Anastassis Ferikoglou, Aggelos Anagnostopoulos, George Xydis, Sotirios Fluid Dynamics Hardware Architecture Computational Fluid Dynamics (CFD) simulations are essential for analyzing and optimizing fluid flows in a wide range of real-world applications. These simulations involve approximating the solutions of the Navier-Stokes differential equations using numerical methods, which are highly compute- and memory-intensive due to their need for high-precision iterations. In this work, we introduce a high-performance FPGA accelerator specifically designed for numerically solving the Navier-Stokes equations. We focus on the Finite Element Method (FEM) due to its ability to accurately model complex geometries and intricate setups typical of real-world applications. Our accelerator is implemented using High-Level Synthesis (HLS) on an AMD Alveo U200 FPGA, leveraging the reconfigurability of FPGAs to offer a flexible and adaptable solution. The proposed solution achieves 7.9x higher performance than optimized Vitis-HLS implementations and 45% lower latency with 3.64x less power compared to a software implementation on a high-end server CPU. This highlights the potential of our approach to solve Navier-Stokes equations more effectively, paving the way for tackling even more challenging CFD simulations in the future. |
| title | Dataflow Optimized Reconfigurable Acceleration for FEM-based CFD Simulations |
| topic | Fluid Dynamics Hardware Architecture |
| url | https://arxiv.org/abs/2411.16245 |