FastFlow: GPU Acceleration of Flow and Depression Routing for Landscape Simulation
Terrain analysis plays an important role in computer graphics, hydrology and geomorphology. In particular, analyzing the path of material flow over a terrain with consideration of local depressions is a precursor to many further tasks in erosion, river formation, and plant ecosystem simulation. For...
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| Vydáno v: | Computer graphics forum Ročník 43; číslo 7 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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Oxford
Blackwell Publishing Ltd
01.10.2024
Wiley |
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| ISSN: | 0167-7055, 1467-8659 |
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| Abstract | Terrain analysis plays an important role in computer graphics, hydrology and geomorphology. In particular, analyzing the path of material flow over a terrain with consideration of local depressions is a precursor to many further tasks in erosion, river formation, and plant ecosystem simulation. For example, fluvial erosion simulation used in terrain modeling computes water discharge to repeatedly locate erosion channels for soil removal and transport. Despite its significance, traditional methods face performance constraints, limiting their broader applicability.
In this paper, we propose a novel GPU flow routing algorithm that computes the water discharge in 𝒪(log n) iterations for a terrain with n vertices (assuming n processors). We also provide a depression routing algorithm to route the water out of local minima formed by depressions in the terrain, which converges in 𝒪(log2 n) iterations. Our implementation of these algorithms leads to a 5× speedup for flow routing and 34 × to 52 × speedup for depression routing compared to previous work on a 10242 terrain, enabling interactive control of terrain simulation. |
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| AbstractList | Terrain analysis plays an important role in computer graphics, hydrology and geomorphology. In particular, analyzing the path of material flow over a terrain with consideration of local depressions is a precursor to many further tasks in erosion, river formation, and plant ecosystem simulation. For example, fluvial erosion simulation used in terrain modeling computes water discharge to repeatedly locate erosion channels for soil removal and transport. Despite its significance, traditional methods face performance constraints, limiting their broader applicability.In this paper, we propose a novel GPU flow routing algorithm that computes the water discharge in O(log n) iterations for a terrain with n vertices (assuming n processors). We also provide a depression routing algorithm to route the water out of local minima formed by depressions in the terrain, which converges in O(log^2 n) iterations. Our implementation of these algorithms leads to a 5x speedup for flow routing and 34x to 52x speedup for depression routing compared to previous work on a 1024^2 terrain, enabling interactive control of terrain simulation. Terrain analysis plays an important role in computer graphics, hydrology and geomorphology. In particular, analyzing the path of material flow over a terrain with consideration of local depressions is a precursor to many further tasks in erosion, river formation, and plant ecosystem simulation. For example, fluvial erosion simulation used in terrain modeling computes water discharge to repeatedly locate erosion channels for soil removal and transport. Despite its significance, traditional methods face performance constraints, limiting their broader applicability. In this paper, we propose a novel GPU flow routing algorithm that computes the water discharge in 𝒪(log n) iterations for a terrain with n vertices (assuming n processors). We also provide a depression routing algorithm to route the water out of local minima formed by depressions in the terrain, which converges in 𝒪(log2 n) iterations. Our implementation of these algorithms leads to a 5× speedup for flow routing and 34 × to 52 × speedup for depression routing compared to previous work on a 10242 terrain, enabling interactive control of terrain simulation. Terrain analysis plays an important role in computer graphics, hydrology and geomorphology. In particular, analyzing the path of material flow over a terrain with consideration of local depressions is a precursor to many further tasks in erosion, river formation, and plant ecosystem simulation. For example, fluvial erosion simulation used in terrain modeling computes water discharge to repeatedly locate erosion channels for soil removal and transport. Despite its significance, traditional methods face performance constraints, limiting their broader applicability. In this paper, we propose a novel GPU flow routing algorithm that computes the water discharge in ( log n) iterations for a terrain with n vertices (assuming n processors). We also provide a depression routing algorithm to route the water out of local minima formed by depressions in the terrain, which converges in ( log 2 n) iterations. Our implementation of these algorithms leads to a 5× speedup for flow routing and 34 × to 52 × speedup for depression routing compared to previous work on a 1024 2 terrain, enabling interactive control of terrain simulation. Terrain analysis plays an important role in computer graphics, hydrology and geomorphology. In particular, analyzing the path of material flow over a terrain with consideration of local depressions is a precursor to many further tasks in erosion, river formation, and plant ecosystem simulation. For example, fluvial erosion simulation used in terrain modeling computes water discharge to repeatedly locate erosion channels for soil removal and transport. Despite its significance, traditional methods face performance constraints, limiting their broader applicability.In this paper, we propose a novel GPU flow routing algorithm that computes the water discharge in ð'ª(log n) iterations for a terrain with n vertices (assuming n processors). We also provide a depression routing algorithm to route the water out of local minima formed by depressions in the terrain, which converges in ð'ª(log2 n) iterations. Our implementation of these algorithms leads to a 5× speedup for flow routing and 34 × to 52 × speedup for depression routing compared to previous work on a 10242 terrain, enabling interactive control of terrain simulation. |
| Author | Finley, Brandon Gain, James Kerbl, Bernhard Cordonnier, Guillaume Jain, Aryamaan |
| Author_xml | – sequence: 1 givenname: Aryamaan orcidid: 0000-0002-4521-2416 surname: Jain fullname: Jain, Aryamaan organization: Inria, Université Côte d'Azur – sequence: 2 givenname: Bernhard orcidid: 0000-0002-5168-8648 surname: Kerbl fullname: Kerbl, Bernhard organization: TU Wien – sequence: 3 givenname: James orcidid: 0000-0002-1699-9619 surname: Gain fullname: Gain, James organization: University of Cape Town – sequence: 4 givenname: Brandon orcidid: 0009-0004-9466-7857 surname: Finley fullname: Finley, Brandon organization: University of Lausanne – sequence: 5 givenname: Guillaume orcidid: 0000-0003-0124-0180 surname: Cordonnier fullname: Cordonnier, Guillaume organization: Inria, Université Côte d'Azur |
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| Keywords | Parallel Terrain Modeling GPU Flow routing Erosion |
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| SubjectTerms | Algorithms Apexes CCS Concepts Computer graphics Computer Science Computing methodologies → Shape modeling Geomorphology Graphics processing units Interactive control Massively parallel algorithms Simulation Soil erosion Terrain analysis Terrain models Water discharge |
| Title | FastFlow: GPU Acceleration of Flow and Depression Routing for Landscape Simulation |
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