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Published in:
Mechanics and Modelling of Turbulence–Combustion Interaction Read chapter Read first chapter

2018 | OriginalPaper | Chapter

3. Turbulent Combustion Simulations with High-Performance Computing

Authors : Hemanth Kolla, Jacqueline H. Chen

Published in: Modeling and Simulation of Turbulent Combustion

Publisher: Springer Singapore

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Abstract

Considering that simulations of turbulent combustion are computationally expensive, this chapter takes a decidedly different perspective, that of high-performance computing (HPC). The cost scaling arguments of non-reacting turbulence simulations are revisited and it is shown that the cost scaling for reacting flows is much more stringent for comparable conditions, making parallel computing and HPC indispensable. Hardware abstractions of typical parallel supercomputers are presented which show that for design of an efficient and optimal program, it is essential to exploit both distributed memory parallelism and shared-memory parallelism, i.e. hierarchical parallelism. Principles of efficient programming at various levels of parallelism are illustrated using archetypal code examples. The vast array of numerical methods, particularly schemes for spatial and temporal discretization, are examined in terms of tradeoffs they present from an HPC perspective. Aspects of data analytics that invariably result from large feature-rich data sets generated by combustion simulations are covered briefly.

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previous chapter Detailed Kinetics in Combustion Simulation: Manifestation, Model Reduction, and Computational Diagnostics
next chapter Direct Numerical Simulations for Combustion Science: Past, Present, and Future
Footnotes
1
This distinction is also referred to sometimes as internode versus intra-node or node-level parallelism.
 
2
Early computer architectures had just a single level of cache between the processor and main memory. However, with the number of processors and their speed, increasing dramatically the current architecture has multiple (upto 3) cache levels. Furthermore, in multicore architectures, some levels of caches are not shared amongst all cores on a node, but subsets of them.
 
3
This is a bit of an illusion. What a program addresses is not directly the physical location of memory but what is known as virtual memory. All arrays are stored contiguously in virtual memory, i.e. the memory addresses of successive elements of an array are contiguous in the virtual address space. The translation of the virtual address space to physical memory addresses is handled by memory management layer of an operating system.
 
4
The Intel compiler suite has a very useful compiler option that generates a detailed vectorization report. When turned on, it generates output to a file that lists every portion of the code that was attempted to be vectorized by the compiler, whether the vectorization was successful and what, if anything, prevented a loop from being vectorized.
 
5
The term multiprocessing is itself very general, simply referring to a system with multiple processors. The multicore nodes commonly found today may be thought to belong a subset known as symmetric multiprocessors (SMP) which strictly means that all the processors share all the memory and I/O resources equally and are orchestrated by one instance of an operating system kernel. The reality may be somewhere in between. Most modern node architectures have multiple sets of multicore CPUs, and they are not all exactly equal since at least one or more layers of memory hierarchy are not equally shared by all the cores. They are better described by a category known as non-uniform memory access (NUMA) nodes.
 
6
NVIDIA, which has pioneered use of GPUs for scientific computing, has developed a full-fledged programming model—CUDA—that provides constructs for the thread hierarchy. The smallest group of threads that execute a common instruction is called a warp and from a performance perspective having all threads in a warp do the same computation without diverging is critical.
 
7
The difference between spectral and pseudo-spectral methods lie in how the nonlinear convective term was handled. In the spectral method, all computations were in the wavenumber space, but pseudo-spectral methods use an intermediate step to transform the velocity Fourier modes to physical space, compute the convective term in the physical space and transform it back to the Fourier space.
 
Literature
Bennett J, Abbasi H, Bremer PT, Grout R, Gyulassy A, Jin T, Klasky S, Kolla H, Parashar M, Pascucci V, Pebay P, Thompson D, Yu H, Zhang F, Chen J (2012) Combining in-situ and in-transit processing to enable extreme-scale scientific analysis. In: International conference on high performance computing, networking, storage and analysis (SC)
Bennett J, Clay R, Baker G, Gamell M, Hollman D, Knight S, Kolla H, Sjaardema G, Slattengren N, Teranishi K, Wilke J, Bettencourt M, Bova S, Franko K, Lin P, Grant R, Hammond S, Olivier S, Kale L, Jain N, Mikida E, Aiken A, Bauer M, Lee W, Slaughter E, Treichler S, Berzins M, Harman T, Humphrey A, Schmidt J, Sunderland D, McCormick P, Gutierrez S, Schulz M, Bhatele A, Boehme D, Bremer PT, Gamblin T (2015) ASC ATDM Level 2 Milestone #5325: asynchronous many-task runtime system analysis and assessment for next generation platforms. Technical report SAND2015-8312, Sandia National Laboratories, Albuquerque, NM
Bray K, Libby PA (1976) Interaction effects in turbulent premixed flames. Phys Fluids 19(11):1687–1701CrossRefMATH
Bruno C, Sankaran V, Kolla H, Chen J (2015) Impact of multi-component diffusion in turbulent combustion using direct numerical simulations. Combust Flame 162:4313–4330CrossRef
Burke M, Chaos M, Ju Y, Dryer F, Klippenstein S (2012) Comprehensive \({\rm H}_2/{\rm O}_2\) kinetic model for high-pressure combustion. Int J Chem Kinet 44:444–474
Chaudhuri S, Kolla H, Dave H, Hawkes E, Chen J, Law C (2017) Flame thickness and conditional scalar dissipation rate in a premixed temporal turbulent reacting jet. Combust Flame 184:273–285CrossRef
Chen JH, Choudhary A, de Supinski B, DeVries M, Hawkes ER, Klasky S, Liao WK, Ma KL, Mellor-Crummey J, Podhorszki N, Sankaran R, Shende S, Yoo CS (2009) Terascale direct numerical simulations of turbulent combustion using S3D. Comput Sci Discov 2:015001
Curran H, Gaffuri P, Pitz W, Westbrook C (2002) A comprehensive modeling study of iso-octane oxidation. Combust Flame 129:253–280CrossRef
Descombes S, Duarte M, Dumont T, Laurent F, Louvet V, Massot M (2014) Analysis of operator splitting in the non-asymptotic regime for nonlinear reaction-diffusion equations. Application to the dynamics of premixed flames. SIAM J Numer Anal 52:1311–1334MathSciNetCrossRefMATH
Echekki T, Chen J (1996) Unsteady strain rate and curvature effects in turbulent premixed methane-air flames. Combust Flame 106:184–202CrossRef
Echekki T, Chen J (2002) High-temperature combustion in autoigniting non-homogeneous hydrogen/air mixtures. Proc Combust Inst 29:2061–2068CrossRef
Franzelli B, Riber E, Sanjose M, Poinsot T (2010) A two-step chemical scheme for kerosene-air premixed flames. Combust Flame 157:1364–1373CrossRef
Gamell M, Teranishi K, Mayo J, Kolla H, Heroux M, Chen J, Parashar M (2017) Modeling and simulating multiple failure masking enabled by local recovery for stencil-based applications at extreme scales. IEEE Trans Parallel Distrib Syst
Gropp W, Lusk E, Skjellum A (1994) Using MPI: portable parallel programming with the message-passing interface. Scientific and engineering computation series. MIT Press
Jenkins K, Cant R (1999) Direct numerical simulation of turbulent flame kernels. In: Knight D, Sakell L (eds) Proceedings of the second AFOSR conference on DNS and LES. Kluwer
Kee R, Rupley F, Miller J (1990) The CHEMKIN thermodynamic data base. Technical report SAND-87-8215B, Sandia National Laboratories
Kee RJ, Dixon-Lewis G, Warnatz J, Coltrin ME, Miller JA (1986) A Fortran computer code package for the evaluation of gas-phase multicomponent transport properties. Technical report SAND86-8246, Sandia National Laboratories
Kolla H, Hawkes E, Kerstein A, Chen J (2014) On velocity and reactive scalar spectra in turbulent premixed flames. J Fluid Mech 754:456–487MathSciNetCrossRefMATH
Kolla H, Zhao XY, Chen J, Swaminathan N (2016) Velocity and reactive scalar dissipation spectra in turbulent premixed flames. Combust Sci Technol 188:1424–1439CrossRef
Luong M, Luo Z, Lu T, Chung S, Yoo C (2013) Direct numerical simulations of the ignition of lean primary reference fuel/air mixtures under HCCI condition. Combust Flame 160:2038–2047CrossRef
Nonaka A, Bell J, Day M, Gilet C, Almgren A, Minion M (2012) A deferred correction coupling strategy for low Mach number flow with complex chemistry. Combust Theory Model
Pei Y, Mehl M, Liu W, Lu T, Pitz W, Som S (2015) A multi-component blend as a diesel fuel surrogate for compression ignition engine applications. J Eng Gas Turbines Power (GTP-15-1057)
Poinsot T, Veynante D (2012) Theoretical and numerical combustion, chapter 1. Edwards
Sankaran R, Hawkes E, Chen J, Lu T, Law C (2007) Structure of a spatially developing turbulent lean methane-air Bunsen flame. Proc Combust Inst 31:1291–1298CrossRef
Treichler S, Bauer M, Bhagatwala A, Borghesi G, Sankaran R, Kolla H, McCormick P, Slaughter E, Lee W, Aiken A, Chen J (2018) S3D-Legion: an exascale software for direct numerical simulation (DNS) of turbulent combustion with complex multicomponent chemistry. In: Straatsma T, Williams KAT (eds) Exascale scientific applications scalability and performance portability, chapter 12. CRC Press
Ye Y, Neuroth T, Sauer F, Ma KL, Borghesi G, Konduri A, Kolla H, Chen J (2016) In situ generated probability distribution functions for interactive post hoc visualization and analysis. In: IEEE sixth symposium on large data analysis and visualization (LDAV)
Metadata
Title
Turbulent Combustion Simulations with High-Performance Computing
Authors
Hemanth Kolla
Jacqueline H. Chen
Copyright Year
2018
Publisher
Springer Singapore
Book
Modeling and Simulation of Turbulent Combustion

Print ISBN: 978-981-10-7409-7

Electronic ISBN: 978-981-10-7410-3

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-981-10-7410-3_3

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