Oscar H. Díaz-Ibarra

We present TChem-atm, a performance-portable approach that enables efficient simulation of chemically detailed and multiphase atmospheric chemistry on modern heterogeneous computing architectures. Unlike previous efforts that rely on architecture-specific code or focus exclusively on gas-phase chemistry, TChem-atm supports fully coupled gas–aerosol systems with execution across CPUs, NVIDIA GPUs, and AMD GPUs through the Kokkos programming model. It integrates the flexible multiphase capabilities of the Community Atmospheric Model Chemistry Package (CAMP) with the high performance kinetic routines of TChem, and includes automatic Jacobian construction with support for a range of stiff ODE solvers. We demonstrate TChem-atm's integration into the particle-resolved aerosol model PartMC and validate its accuracy against the existing PartMC–CAMP implementation, showing agreement within solver tolerances. Performance benchmarks reveal substantial speedups on GPU platforms, particularly for large particle populations, with consistent results across hardware backends. By enabling chemically detailed, multiphase simulations with true performance portability and host-model flexibility, TChem-atm provides a new foundation for next-generation atmospheric models.

We present TChem-atm, a performance-portable approach that enables efficient simulation of chemically detailed and multiphase atmospheric chemistry on modern heterogeneous computing architectures. Unlike previous efforts that rely on architecture-specific code or focus exclusively on gas-phase chemistry, TChem-atm supports fully coupled gas–aerosol systems with execution across CPUs, NVIDIA GPUs, and AMD GPUs through the Kokkos programming model. It integrates the flexible multiphase capabilities of the Community Atmospheric Model Chemistry Package (CAMP) with the high performance kinetic routines of TChem, and includes automatic Jacobian construction with support for a range of stiff ODE solvers. We demonstrate TChem-atm's integration into the particle-resolved aerosol model PartMC and validate its accuracy against the existing PartMC–CAMP implementation, showing agreement within solver tolerances. Performance benchmarks reveal substantial speedups on GPU platforms, particularly for large particle populations, with consistent results across hardware backends. By enabling chemically detailed, multiphase simulations with true performance portability and host-model flexibility, TChem-atm provides a new foundation for next-generation atmospheric models.

We present TChem-atm, a performance-portable approach that enables efficient simulation of chemically detailed and multiphase atmospheric chemistry on modern heterogeneous computing architectures. Unlike previous efforts that rely on architecture-specific code or focus exclusively on gas-phase chemistry, TChem-atm supports fully coupled gas–aerosol systems with execution across CPUs, NVIDIA GPUs, and AMD GPUs through the Kokkos programming model. It integrates the flexible multiphase capabilities of the Community Atmospheric Model Chemistry Package (CAMP) with the high performance kinetic routines of TChem, and includes automatic Jacobian construction with support for a range of stiff ODE solvers. We demonstrate TChem-atm's integration into the particle-resolved aerosol model PartMC and validate its accuracy against the existing PartMC–CAMP implementation, showing agreement within solver tolerances. Performance benchmarks reveal substantial speedups on GPU platforms, particularly for large particle populations, with consistent results across hardware backends. By enabling chemically detailed, multiphase simulations with true performance portability and host-model flexibility, TChem-atm provides a new foundation for next-generation atmospheric models.

We present TChem-atm, a performance-portable approach that enables efficient simulation of chemically detailed and multiphase atmospheric chemistry on modern heterogeneous computing architectures. Unlike previous efforts that rely on architecture-specific code or focus exclusively on gas-phase chemistry, TChem-atm supports fully coupled gas–aerosol systems with execution across CPUs, NVIDIA GPUs, and AMD GPUs through the Kokkos programming model. It integrates the flexible multiphase capabilities of the Community Atmospheric Model Chemistry Package (CAMP) with the high performance kinetic routines of TChem, and includes automatic Jacobian construction with support for a range of stiff ODE solvers. We demonstrate TChem-atm's integration into the particle-resolved aerosol model PartMC and validate its accuracy against the existing PartMC–CAMP implementation, showing agreement within solver tolerances. Performance benchmarks reveal substantial speedups on GPU platforms, particularly for large particle populations, with consistent results across hardware backends. By enabling chemically detailed, multiphase simulations with true performance portability and host-model flexibility, TChem-atm provides a new foundation for next-generation atmospheric models.

We present TChem-atm, a performance-portable approach that enables efficient simulation of chemically detailed and multiphase atmospheric chemistry on modern heterogeneous computing architectures. Unlike previous efforts that rely on architecture-specific code or focus exclusively on gas-phase chemistry, TChem-atm supports fully coupled gas–aerosol systems with execution across CPUs, NVIDIA GPUs, and AMD GPUs through the Kokkos programming model. It integrates the flexible multiphase capabilities of the Community Atmospheric Model Chemistry Package (CAMP) with the high performance kinetic routines of TChem, and includes automatic Jacobian construction with support for a range of stiff ODE solvers. We demonstrate TChem-atm's integration into the particle-resolved aerosol model PartMC and validate its accuracy against the existing PartMC–CAMP implementation, showing agreement within solver tolerances. Performance benchmarks reveal substantial speedups on GPU platforms, particularly for large particle populations, with consistent results across hardware backends. By enabling chemically detailed, multiphase simulations with true performance portability and host-model flexibility, TChem-atm provides a new foundation for next-generation atmospheric models.

We present TChem-atm, a performance-portable approach that enables efficient simulation of chemically detailed and multiphase atmospheric chemistry on modern heterogeneous computing architectures. Unlike previous efforts that rely on architecture-specific code or focus exclusively on gas-phase chemistry, TChem-atm supports fully coupled gas–aerosol systems with execution across CPUs, NVIDIA GPUs, and AMD GPUs through the Kokkos programming model. It integrates the flexible multiphase capabilities of the Community Atmospheric Model Chemistry Package (CAMP) with the high performance kinetic routines of TChem, and includes automatic Jacobian construction with support for a range of stiff ODE solvers. We demonstrate TChem-atm's integration into the particle-resolved aerosol model PartMC and validate its accuracy against the existing PartMC–CAMP implementation, showing agreement within solver tolerances. Performance benchmarks reveal substantial speedups on GPU platforms, particularly for large particle populations, with consistent results across hardware backends. By enabling chemically detailed, multiphase simulations with true performance portability and host-model flexibility, TChem-atm provides a new foundation for next-generation atmospheric models.

We present TChem-atm, a performance-portable approach that enables efficient simulation of chemically detailed and multiphase atmospheric chemistry on modern heterogeneous computing architectures. Unlike previous efforts that rely on architecture-specific code or focus exclusively on gas-phase chemistry, TChem-atm supports fully coupled gas–aerosol systems with execution across CPUs, NVIDIA GPUs, and AMD GPUs through the Kokkos programming model. It integrates the flexible multiphase capabilities of the Community Atmospheric Model Chemistry Package (CAMP) with the high performance kinetic routines of TChem, and includes automatic Jacobian construction with support for a range of stiff ODE solvers. We demonstrate TChem-atm's integration into the particle-resolved aerosol model PartMC and validate its accuracy against the existing PartMC–CAMP implementation, showing agreement within solver tolerances. Performance benchmarks reveal substantial speedups on GPU platforms, particularly for large particle populations, with consistent results across hardware backends. By enabling chemically detailed, multiphase simulations with true performance portability and host-model flexibility, TChem-atm provides a new foundation for next-generation atmospheric models.