Pyrometheus: Symbolic abstractions for XPU and automatically differentiated computation of combustion kinetics and thermodynamics

The cost of combustion simulations is often dominated by the evaluation of net production rates of chemical species and mixture thermodynamics (thermochemistry). Execution on computing accelerators (XPUs) such as graphics processing units (GPUs) can greatly reduce this cost. Established thermochemistry software is not readily portable to such devices, as it sacrifices valuable analytical forms that enable differentiation, sensitivity analysis, and implicit time integration. Symbolic abstractions are developed with corresponding transformations that enable computation on accelerators and automatic differentiation by avoiding premature specification of detail. The software package Pyrometheus is introduced as an implementation of these abstractions and their transformations for combustion thermochemistry. The formulation facilitates code generation from the symbolic representation of a specific thermochemical mechanism in multiple target languages, including Python, C ++ , and Fortran. The generated code processes array-valued expressions, but does not specify their semantics. The semantics are provided by compatible array libraries, including NumPy, Pytato, and Google JAX. Thus, the generated code retains a symbolic representation of the thermochemistry, which enables computation on accelerators and CPUs and facilitates automatic differentiation. The design and operation of the symbolic abstractions and their companion tool, Pyrometheus, are discussed throughout. Roofline demonstrations show that the computation of chemical source terms within MFC, a Fortran-based flow solver we link to Pyrometheus, is performant.

Institutions

Publication Details

Journal
Computer Physics Communications
Published
2025-12-11
DOI
https://doi.org/10.1016/j.cpc.2025.109987
Citations
1
Primary Topic
Combustion and flame dynamics
Type
article
Field-Weighted Citation Impact
1.33
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Pyrometheus: Symbolic abstractions for XPU and automatically differentiated computation of combustion kinetics and thermodynamics

1 citations
Computer Physics Communications
Combustion and flame dynamics
1.33
article

Pyrometheus: Symbolic abstractions for XPU and automatically differentiated computation of combustion kinetics and thermodynamics

article en
1 citations

Abstract

The cost of combustion simulations is often dominated by the evaluation of net production rates of chemical species and mixture thermodynamics (thermochemistry). Execution on computing accelerators (XPUs) such as graphics processing units (GPUs) can greatly reduce this cost. Established thermochemistry software is not readily portable to such devices, as it sacrifices valuable analytical forms that enable differentiation, sensitivity analysis, and implicit time integration. Symbolic abstractions are developed with corresponding transformations that enable computation on accelerators and automatic differentiation by avoiding premature specification of detail. The software package Pyrometheus is introduced as an implementation of these abstractions and their transformations for combustion thermochemistry. The formulation facilitates code generation from the symbolic representation of a specific thermochemical mechanism in multiple target languages, including Python, C ++ , and Fortran. The generated code processes array-valued expressions, but does not specify their semantics. The semantics are provided by compatible array libraries, including NumPy, Pytato, and Google JAX. Thus, the generated code retains a symbolic representation of the thermochemistry, which enables computation on accelerators and CPUs and facilitates automatic differentiation. The design and operation of the symbolic abstractions and their companion tool, Pyrometheus, are discussed throughout. Roofline demonstrations show that the computation of chemical source terms within MFC, a Fortran-based flow solver we link to Pyrometheus, is performant.

Computer Physics CommunicationsVol. 320
Georgia Institute of Technology (US), University of Illinois Urbana-Champaign (US)
Openalex Percentile: Top 15%
Combustion and flame dynamics
1.33
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.