Accelerating and Parallelizing Lagrangian Simulations of Mixing‐Limited Reactive Transport

Recent advances in random walk particle tracking have enabled direct simulation of mixing and reactions by allowing the particles to interact with each other using a multipoint mass transfer scheme. The mass transfer scheme allows separation of mixing and spreading processes, among other advantages,...

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Published in:	Water resources research Vol. 55; no. 4; pp. 3556 - 3566
Main Authors:	Engdahl, Nicholas B., Schmidt, Michael J., Benson, David A.
Format:	Journal Article
Language:	English
Published:	Washington John Wiley & Sons, Inc 01.04.2019 American Geophysical Union (AGU)
Subjects:	Algorithms Chemical reactions Computation Computer applications Computer simulation Mass Mass transfer Methods Organic chemistry Parallel processing parallelization Particle tracking Random walk reactive transport Search algorithms Simulation Solvers water
ISSN:	0043-1397, 1944-7973
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Abstract	Recent advances in random walk particle tracking have enabled direct simulation of mixing and reactions by allowing the particles to interact with each other using a multipoint mass transfer scheme. The mass transfer scheme allows separation of mixing and spreading processes, among other advantages, but it is computationally expensive because its speed depends on the number of interacting particle pairs. This note explores methods for relieving the computational bottleneck caused by the mass transfer step, and we use these algorithms to develop a new parallel, interacting particle model. The new model is a combination of a sparse search algorithm and a novel domain decomposition scheme, both of which offer significant speedup relative to the reference case—even when they are executed serially. We combine the strengths of these methods to create a parallel particle scheme that is highly accurate and efficient with run times that scale as 1/P for a fixed number of particles, where P is the number of computational cores (equivalently, subdomains, in this work) being used. The new parallel model is a significant advance because it enables efficient simulation of large particle ensembles that are needed for environmental simulations and also because it can naturally pair with parallel geochemical solvers to create a practical Lagrangian tool for simulating mixing and reactions in complex chemical systems. Key Points Acceleration methods for random walk based reactive transport simulations are developed Domain decomposition methods for interacting particle simulations are introduced The fully parallel algorithm gives good accuracy, speedup, and scaling for up to 106 particles on 103 cores
AbstractList	Recent advances in random walk particle tracking have enabled direct simulation of mixing and reactions by allowing the particles to interact with each other using a multipoint mass transfer scheme. The mass transfer scheme allows separation of mixing and spreading processes, among other advantages, but it is computationally expensive because its speed depends on the number of interacting particle pairs. This note explores methods for relieving the computational bottleneck caused by the mass transfer step, and we use these algorithms to develop a new parallel, interacting particle model. The new model is a combination of a sparse search algorithm and a novel domain decomposition scheme, both of which offer significant speedup relative to the reference case—even when they are executed serially. We combine the strengths of these methods to create a parallel particle scheme that is highly accurate and efficient with run times that scale as 1/P for a fixed number of particles, where P is the number of computational cores (equivalently, subdomains, in this work) being used. The new parallel model is a significant advance because it enables efficient simulation of large particle ensembles that are needed for environmental simulations and also because it can naturally pair with parallel geochemical solvers to create a practical Lagrangian tool for simulating mixing and reactions in complex chemical systems. Recent advances in random walk particle tracking have enabled direct simulation of mixing and reactions by allowing the particles to interact with each other using a multipoint mass transfer scheme. The mass transfer scheme allows separation of mixing and spreading processes, among other advantages, but it is computationally expensive because its speed depends on the number of interacting particle pairs. This note explores methods for relieving the computational bottleneck caused by the mass transfer step, and we use these algorithms to develop a new parallel, interacting particle model. The new model is a combination of a sparse search algorithm and a novel domain decomposition scheme, both of which offer significant speedup relative to the reference case—even when they are executed serially. We combine the strengths of these methods to create a parallel particle scheme that is highly accurate and efficient with run times that scale as 1/P for a fixed number of particles, where P is the number of computational cores (equivalently, subdomains, in this work) being used. The new parallel model is a significant advance because it enables efficient simulation of large particle ensembles that are needed for environmental simulations and also because it can naturally pair with parallel geochemical solvers to create a practical Lagrangian tool for simulating mixing and reactions in complex chemical systems. Key Points Acceleration methods for random walk based reactive transport simulations are developed Domain decomposition methods for interacting particle simulations are introduced The fully parallel algorithm gives good accuracy, speedup, and scaling for up to 106 particles on 103 cores Recent advances in random walk particle tracking have enabled direct simulation of mixing and reactions by allowing the particles to interact with each other using a multipoint mass transfer scheme. The mass transfer scheme allows separation of mixing and spreading processes, among other advantages, but it is computationally expensive because its speed depends on the number of interacting particle pairs. This note explores methods for relieving the computational bottleneck caused by the mass transfer step, and we use these algorithms to develop a new parallel, interacting particle model. The new model is a combination of a sparse search algorithm and a novel domain decomposition scheme, both of which offer significant speedup relative to the reference case—even when they are executed serially. We combine the strengths of these methods to create a parallel particle scheme that is highly accurate and efficient with run times that scale as 1/ P for a fixed number of particles, where P is the number of computational cores (equivalently, subdomains, in this work) being used. The new parallel model is a significant advance because it enables efficient simulation of large particle ensembles that are needed for environmental simulations and also because it can naturally pair with parallel geochemical solvers to create a practical Lagrangian tool for simulating mixing and reactions in complex chemical systems. Acceleration methods for random walk based reactive transport simulations are developed Domain decomposition methods for interacting particle simulations are introduced The fully parallel algorithm gives good accuracy, speedup, and scaling for up to 10 6 particles on 10 3 cores
Author	Engdahl, Nicholas B. Schmidt, Michael J. Benson, David A.
Author_xml	– sequence: 1 givenname: Nicholas B. orcidid: 0000-0001-7441-6330 surname: Engdahl fullname: Engdahl, Nicholas B. email: nick.engdahl@wsu.edu organization: Washington State University – sequence: 2 givenname: Michael J. orcidid: 0000-0001-9237-7910 surname: Schmidt fullname: Schmidt, Michael J. organization: Colorado School of Mines – sequence: 3 givenname: David A. orcidid: 0000-0001-5652-5197 surname: Benson fullname: Benson, David A. organization: Colorado School of Mines
BackLink	https://www.osti.gov/biblio/1507235$$D View this record in Osti.gov
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SubjectTerms	Algorithms Chemical reactions Computation Computer applications Computer simulation Mass Mass transfer Methods Organic chemistry Parallel processing parallelization Particle tracking Random walk reactive transport Search algorithms Simulation Solvers water
Title	Accelerating and Parallelizing Lagrangian Simulations of Mixing‐Limited Reactive Transport
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