KinetiX：用于化学动力学和传输特性的性能便携式代码生成器

IF 7.2 2区物理与天体物理 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computer Physics Communications Pub Date : 2025-01-30 DOI:10.1016/j.cpc.2025.109504

Bogdan A. Danciu, Christos E. Frouzakis

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引用次数: 0

摘要

我们介绍了KinetiX，一个软件工具包，用于生成化学源项、热力学和混合平均输运性质的计算效率高的燃料特定例程，用于燃烧模拟代码。c++例程是为CPU和GPU架构上的高性能执行而设计的。在cpu上，化学动力学计算通过消除冗余操作和使用数据对齐和循环进行优化，这些数据对齐和循环具有琐碎的访问模式，可以实现自动向量化，从而减少复杂数学运算的延迟。在gpu上，通过循环展开、减少代价高昂的指数计算次数和限制活动变量的数量来提高性能，从而更好地使用寄存器。生成例程的精度与使用Cantera计算的参考值进行对照，最大相对误差低于10−7。我们在AMD和NVIDIA的一些最新CPU和GPU架构上评估内核的性能，即AMD EPYC 9653， AMD MI250X和NVIDIA H100。KinetiX生成的例程优于通用Cantera库，在cpu上实现高达2.4倍的物种生产速率和3.2倍的混合平均传输特性的加速。与PelePhysics （CEPTR）生成的例程相比，KinetiX在cpu上实现了高达2.6倍的速度，在gpu上实现了1.7倍的速度，用于单线程的物种生产速率内核。程序摘要程序标题：KinetiXCPC库链接到程序文件：https://doi.org/10.17632/cjwxfw4btt.1Developer's存储库链接：https://github.com/bogdandanciu/KinetiXLicensing条款：BSD 2- clause编程语言：Python， c++问题的性质：燃烧模拟需要有效的计算化学源项，热力学和运输性质的不同燃料类型。我们面临的挑战是在不影响精度的情况下为cpu和gpu优化这些计算。解决方法：从包含动力学参数、热力学和传输数据的输入文件开始，KinetiX生成特定于燃料的例程，以计算物种生产率、热力学和混合平均传输特性，从而在CPU和GPU架构上实现高性能执行。

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KinetiX: A performance portable code generator for chemical kinetics and transport properties

We present KinetiX, a software toolkit to generate computationally efficient fuel-specific routines for the chemical source term, thermodynamic and mixture-averaged transport properties for use in combustion simulation codes. The C++ routines are designed for high-performance execution on both CPU and GPU architectures. On CPUs, chemical kinetics computations are optimized by eliminating redundant operations and using data alignment and loops with trivial access patterns that enable auto-vectorization, reducing the latency of complex mathematical operations. On GPUs, performance is improved by loop unrolling, reducing the number of costly exponential evaluations and limiting the number of live variables for better register usage. The accuracy of the generated routines is checked against reference values computed using Cantera and the maximum relative errors are below

10^{- 7}

. We evaluate the performance of the kernels on some of the latest CPU and GPU architectures from AMD and NVIDIA, i.e., AMD EPYC 9653, AMD MI250X, and NVIDIA H100. The routines generated by KinetiX outperform the general-purpose Cantera library, achieving speedups of up to 2.4x for species production rates and 3.2x for mixture-averaged transport properties on CPUs. Compared to the routines generated by PelePhysics (CEPTR), KinetiX achieves speedups of up to 2.6x on CPUs and 1.7x on GPUs for the species production rates kernel on a single-threaded basis.

Program summary

Program Title: KinetiX

CPC Library link to program files: https://doi.org/10.17632/cjwxfw4btt.1

Developer's repository link: https://github.com/bogdandanciu/KinetiX

Licensing provisions: BSD 2-clause

Programming language: Python, C++

Nature of problem: Combustion simulations require efficient computation of chemical source terms, thermodynamic and transport properties for diverse fuel types. The challenge is optimizing these computations for both CPUs and GPUs without compromising accuracy.

Solution method: Starting from an input file containing kinetic parameters, thermodynamic and transport data, KinetiX generates fuel-specific routines to compute species production rates, thermodynamic and mixture-averaged transport properties for high-performance execution on both CPU and GPU architectures.

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来源期刊

Computer Physics Communications 物理-计算机：跨学科应用

CiteScore

12.10

自引率

3.20%

发文量

287

审稿时长

5.3 months

期刊介绍： The focus of CPC is on contemporary computational methods and techniques and their implementation, the effectiveness of which will normally be evidenced by the author(s) within the context of a substantive problem in physics. Within this setting CPC publishes two types of paper. Computer Programs in Physics (CPiP) These papers describe significant computer programs to be archived in the CPC Program Library which is held in the Mendeley Data repository. The submitted software must be covered by an approved open source licence. Papers and associated computer programs that address a problem of contemporary interest in physics that cannot be solved by current software are particularly encouraged. Computational Physics Papers (CP) These are research papers in, but are not limited to, the following themes across computational physics and related disciplines. mathematical and numerical methods and algorithms; computational models including those associated with the design, control and analysis of experiments; and algebraic computation. Each will normally include software implementation and performance details. The software implementation should, ideally, be available via GitHub, Zenodo or an institutional repository.In addition, research papers on the impact of advanced computer architecture and special purpose computers on computing in the physical sciences and software topics related to, and of importance in, the physical sciences may be considered.