High-performance multi-GPU solver for describing nonlinear acoustic waves in homogeneous thermoviscous media
•A multi-GPU 3-d solver for modeling ultrasound in thermoviscous media is presented.•The proposed algorithm is based on WENO-Z and third-order Runge–Kutta schemes.•A new multi-GPU communication scheme for the Runge–Kutta scheme is developed.•The optimization process used in developing a single- and...
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Veröffentlicht in: | Computers & fluids 2018-09, Vol.173, p.195-205 |
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description | •A multi-GPU 3-d solver for modeling ultrasound in thermoviscous media is presented.•The proposed algorithm is based on WENO-Z and third-order Runge–Kutta schemes.•A new multi-GPU communication scheme for the Runge–Kutta scheme is developed.•The optimization process used in developing a single- and a multi-GPU solver is detailed.•Simulations using single and multiple GPUs were performed to illustrate the method.
A double-precision numerical solver to describe the propagation of high-intensity ultrasound fluctuations using a novel finite-amplitude compressible acoustic model working in multiple processing units (GPUs) is presented. The present solver is based on a conservative hyperbolic formulation derived from a variational analysis of the compressible Navier–Stokes equations and is implemented using an explicit high-order finite difference strategy. In this work, a WENO–Z reconstruction scheme along with a high-order finite-difference stencil are used to approximate the contributions of convective and diffusive spatial operators, respectively. The spatial operators are then associated to a low–storage Runge–Kutta scheme to integrate the system explicitly in time. The present multi-GPU implementation aims to make the best use of every single GPU and gain optimal performance of the algorithm on the per-node basis. To assess the performance of the present solver, a typical mini-server computer with 4 Tesla K80 dual GPU accelerators is used. The results show that the present formulation scales linearly for large domain problems. Moreover, when compared to an OpenMP implementation running with an i7 processor of 4.2 GHz, this is outperformed by our MPI-GPU implementation by a factor of 99. In this work, the present multi-GPU solver is illustrated with a three-dimensional simulation of a highly-intense focused ultrasound propagation. |
doi_str_mv | 10.1016/j.compfluid.2018.03.008 |
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A double-precision numerical solver to describe the propagation of high-intensity ultrasound fluctuations using a novel finite-amplitude compressible acoustic model working in multiple processing units (GPUs) is presented. The present solver is based on a conservative hyperbolic formulation derived from a variational analysis of the compressible Navier–Stokes equations and is implemented using an explicit high-order finite difference strategy. In this work, a WENO–Z reconstruction scheme along with a high-order finite-difference stencil are used to approximate the contributions of convective and diffusive spatial operators, respectively. The spatial operators are then associated to a low–storage Runge–Kutta scheme to integrate the system explicitly in time. The present multi-GPU implementation aims to make the best use of every single GPU and gain optimal performance of the algorithm on the per-node basis. To assess the performance of the present solver, a typical mini-server computer with 4 Tesla K80 dual GPU accelerators is used. The results show that the present formulation scales linearly for large domain problems. Moreover, when compared to an OpenMP implementation running with an i7 processor of 4.2 GHz, this is outperformed by our MPI-GPU implementation by a factor of 99. In this work, the present multi-GPU solver is illustrated with a three-dimensional simulation of a highly-intense focused ultrasound propagation.</description><identifier>ISSN: 0045-7930</identifier><identifier>EISSN: 1879-0747</identifier><identifier>DOI: 10.1016/j.compfluid.2018.03.008</identifier><language>eng</language><publisher>Amsterdam: Elsevier Ltd</publisher><subject>Accelerators ; Acoustic propagation ; Acoustics ; Compressibility ; Computational fluid dynamics ; Computer peripherals ; Computer simulation ; Finite difference method ; Finite difference methods ; Finite element analysis ; Fluid dynamics ; GPUs ; Graphics processing units ; Mathematical models ; Microprocessors ; Nonlinear acoustics ; Operators ; Perfectly matched layers ; Runge-Kutta method ; Thermoviscous media ; Variations ; WENO–Z methods</subject><ispartof>Computers & fluids, 2018-09, Vol.173, p.195-205</ispartof><rights>2018 Elsevier Ltd</rights><rights>Copyright Elsevier BV Sep 15, 2018</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c343t-430a8c20ef2028ef8b24a74795017023df5457f59b714cf6c7eb6f4c13ab7d683</citedby><cites>FETCH-LOGICAL-c343t-430a8c20ef2028ef8b24a74795017023df5457f59b714cf6c7eb6f4c13ab7d683</cites><orcidid>0000-0002-0609-8139 ; 0000-0002-4046-7890 ; 0000-0002-5800-9951</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.compfluid.2018.03.008$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>315,782,786,3552,27931,27932,46002</link.rule.ids></links><search><creatorcontrib>Diaz, Manuel A.</creatorcontrib><creatorcontrib>Solovchuk, Maxim A.</creatorcontrib><creatorcontrib>Sheu, Tony W.H.</creatorcontrib><title>High-performance multi-GPU solver for describing nonlinear acoustic waves in homogeneous thermoviscous media</title><title>Computers & fluids</title><description>•A multi-GPU 3-d solver for modeling ultrasound in thermoviscous media is presented.•The proposed algorithm is based on WENO-Z and third-order Runge–Kutta schemes.•A new multi-GPU communication scheme for the Runge–Kutta scheme is developed.•The optimization process used in developing a single- and a multi-GPU solver is detailed.•Simulations using single and multiple GPUs were performed to illustrate the method.
A double-precision numerical solver to describe the propagation of high-intensity ultrasound fluctuations using a novel finite-amplitude compressible acoustic model working in multiple processing units (GPUs) is presented. The present solver is based on a conservative hyperbolic formulation derived from a variational analysis of the compressible Navier–Stokes equations and is implemented using an explicit high-order finite difference strategy. In this work, a WENO–Z reconstruction scheme along with a high-order finite-difference stencil are used to approximate the contributions of convective and diffusive spatial operators, respectively. The spatial operators are then associated to a low–storage Runge–Kutta scheme to integrate the system explicitly in time. The present multi-GPU implementation aims to make the best use of every single GPU and gain optimal performance of the algorithm on the per-node basis. 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In this work, the present multi-GPU solver is illustrated with a three-dimensional simulation of a highly-intense focused ultrasound propagation.</description><subject>Accelerators</subject><subject>Acoustic propagation</subject><subject>Acoustics</subject><subject>Compressibility</subject><subject>Computational fluid dynamics</subject><subject>Computer peripherals</subject><subject>Computer simulation</subject><subject>Finite difference method</subject><subject>Finite difference methods</subject><subject>Finite element analysis</subject><subject>Fluid dynamics</subject><subject>GPUs</subject><subject>Graphics processing units</subject><subject>Mathematical models</subject><subject>Microprocessors</subject><subject>Nonlinear acoustics</subject><subject>Operators</subject><subject>Perfectly matched layers</subject><subject>Runge-Kutta method</subject><subject>Thermoviscous media</subject><subject>Variations</subject><subject>WENO–Z methods</subject><issn>0045-7930</issn><issn>1879-0747</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNqFkFtLxDAQhYMouF5-gwGfWyeXbtpHEW8g6IM-hzSd7GZpmzVpV_z3Zlnx1adhZs6Z4XyEXDEoGbDlzaa0Ydi6fvZdyYHVJYgSoD4iC1arpgAl1TFZAMiqUI2AU3KW0gZyL7hckP7Jr9bFFqMLcTCjRTrM_eSLx7cPmkK_w0jzhnaYbPStH1d0DGPvRzSRGhvmNHlLv8wOE_UjXYchrHDEPKfTGuMQdj7tVXTAzpsLcuJMn_Dyt56Tj4f797un4uX18fnu9qWwQoqpkAJMbTmg48BrdHXLpckxmgqYAi46V8lKuappFZPWLa3CdumkZcK0qlvW4pxcH-5uY_icMU16E-Y45peaMyY5a6Daq9RBZWNIKaLT2-gHE781A71Hqzf6D63eo9UgdEabnbcHJ-YQO49RJ-sxw-t8RDvpLvh_b_wAZN-IfQ</recordid><startdate>20180915</startdate><enddate>20180915</enddate><creator>Diaz, Manuel A.</creator><creator>Solovchuk, Maxim A.</creator><creator>Sheu, Tony W.H.</creator><general>Elsevier Ltd</general><general>Elsevier BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7TB</scope><scope>7U5</scope><scope>8FD</scope><scope>FR3</scope><scope>H8D</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0002-0609-8139</orcidid><orcidid>https://orcid.org/0000-0002-4046-7890</orcidid><orcidid>https://orcid.org/0000-0002-5800-9951</orcidid></search><sort><creationdate>20180915</creationdate><title>High-performance multi-GPU solver for describing nonlinear acoustic waves in homogeneous thermoviscous media</title><author>Diaz, Manuel A. ; Solovchuk, Maxim A. ; Sheu, Tony W.H.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c343t-430a8c20ef2028ef8b24a74795017023df5457f59b714cf6c7eb6f4c13ab7d683</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Accelerators</topic><topic>Acoustic propagation</topic><topic>Acoustics</topic><topic>Compressibility</topic><topic>Computational fluid dynamics</topic><topic>Computer peripherals</topic><topic>Computer simulation</topic><topic>Finite difference method</topic><topic>Finite difference methods</topic><topic>Finite element analysis</topic><topic>Fluid dynamics</topic><topic>GPUs</topic><topic>Graphics processing units</topic><topic>Mathematical models</topic><topic>Microprocessors</topic><topic>Nonlinear acoustics</topic><topic>Operators</topic><topic>Perfectly matched layers</topic><topic>Runge-Kutta method</topic><topic>Thermoviscous media</topic><topic>Variations</topic><topic>WENO–Z methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Diaz, Manuel A.</creatorcontrib><creatorcontrib>Solovchuk, Maxim A.</creatorcontrib><creatorcontrib>Sheu, Tony W.H.</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Computers & fluids</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Diaz, Manuel A.</au><au>Solovchuk, Maxim A.</au><au>Sheu, Tony W.H.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>High-performance multi-GPU solver for describing nonlinear acoustic waves in homogeneous thermoviscous media</atitle><jtitle>Computers & fluids</jtitle><date>2018-09-15</date><risdate>2018</risdate><volume>173</volume><spage>195</spage><epage>205</epage><pages>195-205</pages><issn>0045-7930</issn><eissn>1879-0747</eissn><abstract>•A multi-GPU 3-d solver for modeling ultrasound in thermoviscous media is presented.•The proposed algorithm is based on WENO-Z and third-order Runge–Kutta schemes.•A new multi-GPU communication scheme for the Runge–Kutta scheme is developed.•The optimization process used in developing a single- and a multi-GPU solver is detailed.•Simulations using single and multiple GPUs were performed to illustrate the method.
A double-precision numerical solver to describe the propagation of high-intensity ultrasound fluctuations using a novel finite-amplitude compressible acoustic model working in multiple processing units (GPUs) is presented. The present solver is based on a conservative hyperbolic formulation derived from a variational analysis of the compressible Navier–Stokes equations and is implemented using an explicit high-order finite difference strategy. In this work, a WENO–Z reconstruction scheme along with a high-order finite-difference stencil are used to approximate the contributions of convective and diffusive spatial operators, respectively. The spatial operators are then associated to a low–storage Runge–Kutta scheme to integrate the system explicitly in time. The present multi-GPU implementation aims to make the best use of every single GPU and gain optimal performance of the algorithm on the per-node basis. To assess the performance of the present solver, a typical mini-server computer with 4 Tesla K80 dual GPU accelerators is used. The results show that the present formulation scales linearly for large domain problems. Moreover, when compared to an OpenMP implementation running with an i7 processor of 4.2 GHz, this is outperformed by our MPI-GPU implementation by a factor of 99. In this work, the present multi-GPU solver is illustrated with a three-dimensional simulation of a highly-intense focused ultrasound propagation.</abstract><cop>Amsterdam</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.compfluid.2018.03.008</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-0609-8139</orcidid><orcidid>https://orcid.org/0000-0002-4046-7890</orcidid><orcidid>https://orcid.org/0000-0002-5800-9951</orcidid></addata></record> |
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subjects | Accelerators Acoustic propagation Acoustics Compressibility Computational fluid dynamics Computer peripherals Computer simulation Finite difference method Finite difference methods Finite element analysis Fluid dynamics GPUs Graphics processing units Mathematical models Microprocessors Nonlinear acoustics Operators Perfectly matched layers Runge-Kutta method Thermoviscous media Variations WENO–Z methods |
title | High-performance multi-GPU solver for describing nonlinear acoustic waves in homogeneous thermoviscous media |
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