Billion degree of freedom granular dynamics simulation on commodity hardware via heterogeneous data-type representation

Granular to run billion-degree-of-freedom dynamics problems on commodity hardware, i.e., a workstation with one GPU. The ability to scale the solution to large problem sizes is traced back to an adimensionalization process combined with the use of mixed-precision data types that reduce memory pressu...
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Autor*in:	Kelly, Conlain [verfasserIn] Olsen, Nicholas [verfasserIn] Negrut, Dan [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	Many-body dynamics GPU parallel computing Friction and contact Discrete element method Granular material

Übergeordnetes Werk:	Enthalten in: Multibody system dynamics - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1997, 50(2020), 4 vom: 03. Juni, Seite 355-379
Übergeordnetes Werk:	volume:50 ; year:2020 ; number:4 ; day:03 ; month:06 ; pages:355-379

Links:	Volltext

DOI / URN:	10.1007/s11044-020-09749-7

Katalog-ID:	SPR041941330

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520			\|a Abstract We discuss modeling, algorithmic, and software aspects that allow a simulation tool called Chrono::Granular to run billion-degree-of-freedom dynamics problems on commodity hardware, i.e., a workstation with one GPU. The ability to scale the solution to large problem sizes is traced back to an adimensionalization process combined with the use of mixed-precision data types that reduce memory pressure and improve arithmetic intensity, judicious use of the memory ecosystem on GPU cards as exposed by CUDA on Nvidia architectures, and a software implementation that prioritizes execution speed over modeling generality. The simulation approach is demonstrated for 3D scenarios with up to 710 million bodies for the frictionless case (of relevance in emulsions), and up to 210 million bodies for scenarios with friction (of relevance in terradynamics, additive manufacturing, soft-matter physics). The frictional contact model used draws on the Discrete Element Method (DEM). A performance benchmark shows linear scaling with problem size up to GPU memory capacity. The implementation has an application programming interface that enables it to interact in a cosimulation framework with third-party dynamics engines. This interaction is anchored by a force–displacement data exchange protocol that brings in external bodies as geometries defined by triangle meshes. We demonstrate the cosimulation mechanism by interfacing to an open source, multiphysics simulation engine called Chrono. Therein, triangular meshes define moving boundary conditions for Chrono::Granular, which in turn provides forces and torques acting on the triangular meshes. Several tests are considered for validation and scaling analysis purposes. The limiting aspects of the current implementation are its exclusive support of monodisperse granular systems, and its lack of handling geometries beyond spheres. These limitations are addressed by ongoing work.
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700	1		\|a Negrut, Dan \|e verfasserin \|4 aut
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author_variant	c k ck n o no d n dn
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allfields	10.1007/s11044-020-09749-7 doi (DE-627)SPR041941330 (SPR)s11044-020-09749-7-e DE-627 ger DE-627 rakwb eng 600 ASE 50.32 bkl Kelly, Conlain verfasserin aut Billion degree of freedom granular dynamics simulation on commodity hardware via heterogeneous data-type representation 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract We discuss modeling, algorithmic, and software aspects that allow a simulation tool called Chrono::Granular to run billion-degree-of-freedom dynamics problems on commodity hardware, i.e., a workstation with one GPU. The ability to scale the solution to large problem sizes is traced back to an adimensionalization process combined with the use of mixed-precision data types that reduce memory pressure and improve arithmetic intensity, judicious use of the memory ecosystem on GPU cards as exposed by CUDA on Nvidia architectures, and a software implementation that prioritizes execution speed over modeling generality. The simulation approach is demonstrated for 3D scenarios with up to 710 million bodies for the frictionless case (of relevance in emulsions), and up to 210 million bodies for scenarios with friction (of relevance in terradynamics, additive manufacturing, soft-matter physics). The frictional contact model used draws on the Discrete Element Method (DEM). A performance benchmark shows linear scaling with problem size up to GPU memory capacity. The implementation has an application programming interface that enables it to interact in a cosimulation framework with third-party dynamics engines. This interaction is anchored by a force–displacement data exchange protocol that brings in external bodies as geometries defined by triangle meshes. We demonstrate the cosimulation mechanism by interfacing to an open source, multiphysics simulation engine called Chrono. Therein, triangular meshes define moving boundary conditions for Chrono::Granular, which in turn provides forces and torques acting on the triangular meshes. Several tests are considered for validation and scaling analysis purposes. The limiting aspects of the current implementation are its exclusive support of monodisperse granular systems, and its lack of handling geometries beyond spheres. These limitations are addressed by ongoing work. Many-body dynamics (dpeaa)DE-He213 GPU parallel computing (dpeaa)DE-He213 Friction and contact (dpeaa)DE-He213 Discrete element method (dpeaa)DE-He213 Granular material (dpeaa)DE-He213 Olsen, Nicholas verfasserin aut Negrut, Dan verfasserin aut Enthalten in Multibody system dynamics Dordrecht [u.a.] : Springer Science + Business Media B.V, 1997 50(2020), 4 vom: 03. Juni, Seite 355-379 (DE-627)271181087 (DE-600)1479537-1 1573-272X nnns volume:50 year:2020 number:4 day:03 month:06 pages:355-379 https://dx.doi.org/10.1007/s11044-020-09749-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.32 ASE AR 50 2020 4 03 06 355-379
spelling	10.1007/s11044-020-09749-7 doi (DE-627)SPR041941330 (SPR)s11044-020-09749-7-e DE-627 ger DE-627 rakwb eng 600 ASE 50.32 bkl Kelly, Conlain verfasserin aut Billion degree of freedom granular dynamics simulation on commodity hardware via heterogeneous data-type representation 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract We discuss modeling, algorithmic, and software aspects that allow a simulation tool called Chrono::Granular to run billion-degree-of-freedom dynamics problems on commodity hardware, i.e., a workstation with one GPU. The ability to scale the solution to large problem sizes is traced back to an adimensionalization process combined with the use of mixed-precision data types that reduce memory pressure and improve arithmetic intensity, judicious use of the memory ecosystem on GPU cards as exposed by CUDA on Nvidia architectures, and a software implementation that prioritizes execution speed over modeling generality. The simulation approach is demonstrated for 3D scenarios with up to 710 million bodies for the frictionless case (of relevance in emulsions), and up to 210 million bodies for scenarios with friction (of relevance in terradynamics, additive manufacturing, soft-matter physics). The frictional contact model used draws on the Discrete Element Method (DEM). A performance benchmark shows linear scaling with problem size up to GPU memory capacity. The implementation has an application programming interface that enables it to interact in a cosimulation framework with third-party dynamics engines. This interaction is anchored by a force–displacement data exchange protocol that brings in external bodies as geometries defined by triangle meshes. We demonstrate the cosimulation mechanism by interfacing to an open source, multiphysics simulation engine called Chrono. Therein, triangular meshes define moving boundary conditions for Chrono::Granular, which in turn provides forces and torques acting on the triangular meshes. Several tests are considered for validation and scaling analysis purposes. The limiting aspects of the current implementation are its exclusive support of monodisperse granular systems, and its lack of handling geometries beyond spheres. These limitations are addressed by ongoing work. Many-body dynamics (dpeaa)DE-He213 GPU parallel computing (dpeaa)DE-He213 Friction and contact (dpeaa)DE-He213 Discrete element method (dpeaa)DE-He213 Granular material (dpeaa)DE-He213 Olsen, Nicholas verfasserin aut Negrut, Dan verfasserin aut Enthalten in Multibody system dynamics Dordrecht [u.a.] : Springer Science + Business Media B.V, 1997 50(2020), 4 vom: 03. Juni, Seite 355-379 (DE-627)271181087 (DE-600)1479537-1 1573-272X nnns volume:50 year:2020 number:4 day:03 month:06 pages:355-379 https://dx.doi.org/10.1007/s11044-020-09749-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.32 ASE AR 50 2020 4 03 06 355-379
allfields_unstemmed	10.1007/s11044-020-09749-7 doi (DE-627)SPR041941330 (SPR)s11044-020-09749-7-e DE-627 ger DE-627 rakwb eng 600 ASE 50.32 bkl Kelly, Conlain verfasserin aut Billion degree of freedom granular dynamics simulation on commodity hardware via heterogeneous data-type representation 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract We discuss modeling, algorithmic, and software aspects that allow a simulation tool called Chrono::Granular to run billion-degree-of-freedom dynamics problems on commodity hardware, i.e., a workstation with one GPU. The ability to scale the solution to large problem sizes is traced back to an adimensionalization process combined with the use of mixed-precision data types that reduce memory pressure and improve arithmetic intensity, judicious use of the memory ecosystem on GPU cards as exposed by CUDA on Nvidia architectures, and a software implementation that prioritizes execution speed over modeling generality. The simulation approach is demonstrated for 3D scenarios with up to 710 million bodies for the frictionless case (of relevance in emulsions), and up to 210 million bodies for scenarios with friction (of relevance in terradynamics, additive manufacturing, soft-matter physics). The frictional contact model used draws on the Discrete Element Method (DEM). A performance benchmark shows linear scaling with problem size up to GPU memory capacity. The implementation has an application programming interface that enables it to interact in a cosimulation framework with third-party dynamics engines. This interaction is anchored by a force–displacement data exchange protocol that brings in external bodies as geometries defined by triangle meshes. We demonstrate the cosimulation mechanism by interfacing to an open source, multiphysics simulation engine called Chrono. Therein, triangular meshes define moving boundary conditions for Chrono::Granular, which in turn provides forces and torques acting on the triangular meshes. Several tests are considered for validation and scaling analysis purposes. The limiting aspects of the current implementation are its exclusive support of monodisperse granular systems, and its lack of handling geometries beyond spheres. These limitations are addressed by ongoing work. Many-body dynamics (dpeaa)DE-He213 GPU parallel computing (dpeaa)DE-He213 Friction and contact (dpeaa)DE-He213 Discrete element method (dpeaa)DE-He213 Granular material (dpeaa)DE-He213 Olsen, Nicholas verfasserin aut Negrut, Dan verfasserin aut Enthalten in Multibody system dynamics Dordrecht [u.a.] : Springer Science + Business Media B.V, 1997 50(2020), 4 vom: 03. Juni, Seite 355-379 (DE-627)271181087 (DE-600)1479537-1 1573-272X nnns volume:50 year:2020 number:4 day:03 month:06 pages:355-379 https://dx.doi.org/10.1007/s11044-020-09749-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.32 ASE AR 50 2020 4 03 06 355-379
allfieldsGer	10.1007/s11044-020-09749-7 doi (DE-627)SPR041941330 (SPR)s11044-020-09749-7-e DE-627 ger DE-627 rakwb eng 600 ASE 50.32 bkl Kelly, Conlain verfasserin aut Billion degree of freedom granular dynamics simulation on commodity hardware via heterogeneous data-type representation 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract We discuss modeling, algorithmic, and software aspects that allow a simulation tool called Chrono::Granular to run billion-degree-of-freedom dynamics problems on commodity hardware, i.e., a workstation with one GPU. The ability to scale the solution to large problem sizes is traced back to an adimensionalization process combined with the use of mixed-precision data types that reduce memory pressure and improve arithmetic intensity, judicious use of the memory ecosystem on GPU cards as exposed by CUDA on Nvidia architectures, and a software implementation that prioritizes execution speed over modeling generality. The simulation approach is demonstrated for 3D scenarios with up to 710 million bodies for the frictionless case (of relevance in emulsions), and up to 210 million bodies for scenarios with friction (of relevance in terradynamics, additive manufacturing, soft-matter physics). The frictional contact model used draws on the Discrete Element Method (DEM). A performance benchmark shows linear scaling with problem size up to GPU memory capacity. The implementation has an application programming interface that enables it to interact in a cosimulation framework with third-party dynamics engines. This interaction is anchored by a force–displacement data exchange protocol that brings in external bodies as geometries defined by triangle meshes. We demonstrate the cosimulation mechanism by interfacing to an open source, multiphysics simulation engine called Chrono. Therein, triangular meshes define moving boundary conditions for Chrono::Granular, which in turn provides forces and torques acting on the triangular meshes. Several tests are considered for validation and scaling analysis purposes. The limiting aspects of the current implementation are its exclusive support of monodisperse granular systems, and its lack of handling geometries beyond spheres. These limitations are addressed by ongoing work. Many-body dynamics (dpeaa)DE-He213 GPU parallel computing (dpeaa)DE-He213 Friction and contact (dpeaa)DE-He213 Discrete element method (dpeaa)DE-He213 Granular material (dpeaa)DE-He213 Olsen, Nicholas verfasserin aut Negrut, Dan verfasserin aut Enthalten in Multibody system dynamics Dordrecht [u.a.] : Springer Science + Business Media B.V, 1997 50(2020), 4 vom: 03. Juni, Seite 355-379 (DE-627)271181087 (DE-600)1479537-1 1573-272X nnns volume:50 year:2020 number:4 day:03 month:06 pages:355-379 https://dx.doi.org/10.1007/s11044-020-09749-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.32 ASE AR 50 2020 4 03 06 355-379
allfieldsSound	10.1007/s11044-020-09749-7 doi (DE-627)SPR041941330 (SPR)s11044-020-09749-7-e DE-627 ger DE-627 rakwb eng 600 ASE 50.32 bkl Kelly, Conlain verfasserin aut Billion degree of freedom granular dynamics simulation on commodity hardware via heterogeneous data-type representation 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract We discuss modeling, algorithmic, and software aspects that allow a simulation tool called Chrono::Granular to run billion-degree-of-freedom dynamics problems on commodity hardware, i.e., a workstation with one GPU. The ability to scale the solution to large problem sizes is traced back to an adimensionalization process combined with the use of mixed-precision data types that reduce memory pressure and improve arithmetic intensity, judicious use of the memory ecosystem on GPU cards as exposed by CUDA on Nvidia architectures, and a software implementation that prioritizes execution speed over modeling generality. The simulation approach is demonstrated for 3D scenarios with up to 710 million bodies for the frictionless case (of relevance in emulsions), and up to 210 million bodies for scenarios with friction (of relevance in terradynamics, additive manufacturing, soft-matter physics). The frictional contact model used draws on the Discrete Element Method (DEM). A performance benchmark shows linear scaling with problem size up to GPU memory capacity. The implementation has an application programming interface that enables it to interact in a cosimulation framework with third-party dynamics engines. This interaction is anchored by a force–displacement data exchange protocol that brings in external bodies as geometries defined by triangle meshes. We demonstrate the cosimulation mechanism by interfacing to an open source, multiphysics simulation engine called Chrono. Therein, triangular meshes define moving boundary conditions for Chrono::Granular, which in turn provides forces and torques acting on the triangular meshes. Several tests are considered for validation and scaling analysis purposes. The limiting aspects of the current implementation are its exclusive support of monodisperse granular systems, and its lack of handling geometries beyond spheres. These limitations are addressed by ongoing work. Many-body dynamics (dpeaa)DE-He213 GPU parallel computing (dpeaa)DE-He213 Friction and contact (dpeaa)DE-He213 Discrete element method (dpeaa)DE-He213 Granular material (dpeaa)DE-He213 Olsen, Nicholas verfasserin aut Negrut, Dan verfasserin aut Enthalten in Multibody system dynamics Dordrecht [u.a.] : Springer Science + Business Media B.V, 1997 50(2020), 4 vom: 03. Juni, Seite 355-379 (DE-627)271181087 (DE-600)1479537-1 1573-272X nnns volume:50 year:2020 number:4 day:03 month:06 pages:355-379 https://dx.doi.org/10.1007/s11044-020-09749-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.32 ASE AR 50 2020 4 03 06 355-379
language	English
source	Enthalten in Multibody system dynamics 50(2020), 4 vom: 03. Juni, Seite 355-379 volume:50 year:2020 number:4 day:03 month:06 pages:355-379
sourceStr	Enthalten in Multibody system dynamics 50(2020), 4 vom: 03. Juni, Seite 355-379 volume:50 year:2020 number:4 day:03 month:06 pages:355-379
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Many-body dynamics GPU parallel computing Friction and contact Discrete element method Granular material
dewey-raw	600
isfreeaccess_bool	false
container_title	Multibody system dynamics
authorswithroles_txt_mv	Kelly, Conlain @@aut@@ Olsen, Nicholas @@aut@@ Negrut, Dan @@aut@@
publishDateDaySort_date	2020-06-03T00:00:00Z
hierarchy_top_id	271181087
dewey-sort	3600
id	SPR041941330
language_de	englisch
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author	Kelly, Conlain
spellingShingle	Kelly, Conlain ddc 600 bkl 50.32 misc Many-body dynamics misc GPU parallel computing misc Friction and contact misc Discrete element method misc Granular material Billion degree of freedom granular dynamics simulation on commodity hardware via heterogeneous data-type representation
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topic_title	600 ASE 50.32 bkl Billion degree of freedom granular dynamics simulation on commodity hardware via heterogeneous data-type representation Many-body dynamics (dpeaa)DE-He213 GPU parallel computing (dpeaa)DE-He213 Friction and contact (dpeaa)DE-He213 Discrete element method (dpeaa)DE-He213 Granular material (dpeaa)DE-He213
topic	ddc 600 bkl 50.32 misc Many-body dynamics misc GPU parallel computing misc Friction and contact misc Discrete element method misc Granular material
topic_unstemmed	ddc 600 bkl 50.32 misc Many-body dynamics misc GPU parallel computing misc Friction and contact misc Discrete element method misc Granular material
topic_browse	ddc 600 bkl 50.32 misc Many-body dynamics misc GPU parallel computing misc Friction and contact misc Discrete element method misc Granular material
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title	Billion degree of freedom granular dynamics simulation on commodity hardware via heterogeneous data-type representation
ctrlnum	(DE-627)SPR041941330 (SPR)s11044-020-09749-7-e
title_full	Billion degree of freedom granular dynamics simulation on commodity hardware via heterogeneous data-type representation
author_sort	Kelly, Conlain
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author_browse	Kelly, Conlain Olsen, Nicholas Negrut, Dan
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title_sort	billion degree of freedom granular dynamics simulation on commodity hardware via heterogeneous data-type representation
title_auth	Billion degree of freedom granular dynamics simulation on commodity hardware via heterogeneous data-type representation
abstract	Abstract We discuss modeling, algorithmic, and software aspects that allow a simulation tool called Chrono::Granular to run billion-degree-of-freedom dynamics problems on commodity hardware, i.e., a workstation with one GPU. The ability to scale the solution to large problem sizes is traced back to an adimensionalization process combined with the use of mixed-precision data types that reduce memory pressure and improve arithmetic intensity, judicious use of the memory ecosystem on GPU cards as exposed by CUDA on Nvidia architectures, and a software implementation that prioritizes execution speed over modeling generality. The simulation approach is demonstrated for 3D scenarios with up to 710 million bodies for the frictionless case (of relevance in emulsions), and up to 210 million bodies for scenarios with friction (of relevance in terradynamics, additive manufacturing, soft-matter physics). The frictional contact model used draws on the Discrete Element Method (DEM). A performance benchmark shows linear scaling with problem size up to GPU memory capacity. The implementation has an application programming interface that enables it to interact in a cosimulation framework with third-party dynamics engines. This interaction is anchored by a force–displacement data exchange protocol that brings in external bodies as geometries defined by triangle meshes. We demonstrate the cosimulation mechanism by interfacing to an open source, multiphysics simulation engine called Chrono. Therein, triangular meshes define moving boundary conditions for Chrono::Granular, which in turn provides forces and torques acting on the triangular meshes. Several tests are considered for validation and scaling analysis purposes. The limiting aspects of the current implementation are its exclusive support of monodisperse granular systems, and its lack of handling geometries beyond spheres. These limitations are addressed by ongoing work.
abstractGer	Abstract We discuss modeling, algorithmic, and software aspects that allow a simulation tool called Chrono::Granular to run billion-degree-of-freedom dynamics problems on commodity hardware, i.e., a workstation with one GPU. The ability to scale the solution to large problem sizes is traced back to an adimensionalization process combined with the use of mixed-precision data types that reduce memory pressure and improve arithmetic intensity, judicious use of the memory ecosystem on GPU cards as exposed by CUDA on Nvidia architectures, and a software implementation that prioritizes execution speed over modeling generality. The simulation approach is demonstrated for 3D scenarios with up to 710 million bodies for the frictionless case (of relevance in emulsions), and up to 210 million bodies for scenarios with friction (of relevance in terradynamics, additive manufacturing, soft-matter physics). The frictional contact model used draws on the Discrete Element Method (DEM). A performance benchmark shows linear scaling with problem size up to GPU memory capacity. The implementation has an application programming interface that enables it to interact in a cosimulation framework with third-party dynamics engines. This interaction is anchored by a force–displacement data exchange protocol that brings in external bodies as geometries defined by triangle meshes. We demonstrate the cosimulation mechanism by interfacing to an open source, multiphysics simulation engine called Chrono. Therein, triangular meshes define moving boundary conditions for Chrono::Granular, which in turn provides forces and torques acting on the triangular meshes. Several tests are considered for validation and scaling analysis purposes. The limiting aspects of the current implementation are its exclusive support of monodisperse granular systems, and its lack of handling geometries beyond spheres. These limitations are addressed by ongoing work.
abstract_unstemmed	Abstract We discuss modeling, algorithmic, and software aspects that allow a simulation tool called Chrono::Granular to run billion-degree-of-freedom dynamics problems on commodity hardware, i.e., a workstation with one GPU. The ability to scale the solution to large problem sizes is traced back to an adimensionalization process combined with the use of mixed-precision data types that reduce memory pressure and improve arithmetic intensity, judicious use of the memory ecosystem on GPU cards as exposed by CUDA on Nvidia architectures, and a software implementation that prioritizes execution speed over modeling generality. The simulation approach is demonstrated for 3D scenarios with up to 710 million bodies for the frictionless case (of relevance in emulsions), and up to 210 million bodies for scenarios with friction (of relevance in terradynamics, additive manufacturing, soft-matter physics). The frictional contact model used draws on the Discrete Element Method (DEM). A performance benchmark shows linear scaling with problem size up to GPU memory capacity. The implementation has an application programming interface that enables it to interact in a cosimulation framework with third-party dynamics engines. This interaction is anchored by a force–displacement data exchange protocol that brings in external bodies as geometries defined by triangle meshes. We demonstrate the cosimulation mechanism by interfacing to an open source, multiphysics simulation engine called Chrono. Therein, triangular meshes define moving boundary conditions for Chrono::Granular, which in turn provides forces and torques acting on the triangular meshes. Several tests are considered for validation and scaling analysis purposes. The limiting aspects of the current implementation are its exclusive support of monodisperse granular systems, and its lack of handling geometries beyond spheres. These limitations are addressed by ongoing work.
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title_short	Billion degree of freedom granular dynamics simulation on commodity hardware via heterogeneous data-type representation
url	https://dx.doi.org/10.1007/s11044-020-09749-7
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author2	Olsen, Nicholas Negrut, Dan
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doi_str	10.1007/s11044-020-09749-7
up_date	2024-07-04T00:13:14.328Z
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fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR041941330</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220111024922.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201113s2020 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s11044-020-09749-7</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR041941330</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s11044-020-09749-7-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">600</subfield><subfield code="q">ASE</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">50.32</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Kelly, Conlain</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Billion degree of freedom granular dynamics simulation on commodity hardware via heterogeneous data-type representation</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2020</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract We discuss modeling, algorithmic, and software aspects that allow a simulation tool called Chrono::Granular to run billion-degree-of-freedom dynamics problems on commodity hardware, i.e., a workstation with one GPU. The ability to scale the solution to large problem sizes is traced back to an adimensionalization process combined with the use of mixed-precision data types that reduce memory pressure and improve arithmetic intensity, judicious use of the memory ecosystem on GPU cards as exposed by CUDA on Nvidia architectures, and a software implementation that prioritizes execution speed over modeling generality. The simulation approach is demonstrated for 3D scenarios with up to 710 million bodies for the frictionless case (of relevance in emulsions), and up to 210 million bodies for scenarios with friction (of relevance in terradynamics, additive manufacturing, soft-matter physics). The frictional contact model used draws on the Discrete Element Method (DEM). A performance benchmark shows linear scaling with problem size up to GPU memory capacity. The implementation has an application programming interface that enables it to interact in a cosimulation framework with third-party dynamics engines. This interaction is anchored by a force–displacement data exchange protocol that brings in external bodies as geometries defined by triangle meshes. We demonstrate the cosimulation mechanism by interfacing to an open source, multiphysics simulation engine called Chrono. Therein, triangular meshes define moving boundary conditions for Chrono::Granular, which in turn provides forces and torques acting on the triangular meshes. Several tests are considered for validation and scaling analysis purposes. The limiting aspects of the current implementation are its exclusive support of monodisperse granular systems, and its lack of handling geometries beyond spheres. 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