  Earth system models (ESM) demand significant hardware resources and energy
consumption to solve atmospheric chemistry processes. Recent studies have shown
improved performance from running these models on GPU accelerators.
Nonetheless, there is room for improvement in exploiting even more GPU
resources.
  This study proposes an optimized distribution of the chemical solver's
computational load on the GPU, named Block-cells. Additionally, we evaluate
different configurations for distributing the computational load in an NVIDIA
GPU.
  We use the linear solver from the Chemistry Across Multiple Phases (CAMP)
framework as our test bed. An intermediate-complexity chemical mechanism under
typical atmospheric conditions is used. Results demonstrate a 35x speedup
compared to the single-CPU thread reference case. Even using the full resources
of the node (40 physical cores) on the reference case, the Block-cells version
outperforms them by 50%. The Block-cells approach shows promise in alleviating
the computational burden of chemical solvers on GPU architectures.
