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.

翻译：地球系统模型在求解大气化学过程时需要消耗大量硬件资源和能源。近期研究表明，在GPU加速器上运行此类模型可显著提升性能。然而，在进一步利用GPU资源方面仍存在优化空间。本研究提出一种在GPU上优化分配化学求解器计算负载的方法，命名为Block-cells。此外，我们评估了在NVIDIA GPU上分配计算负载的不同配置方案。我们以多相化学框架中的线性求解器作为测试平台，并采用典型大气条件下的中等复杂度化学机制进行验证。实验结果表明，相较于单CPU线程基准案例，该方法实现了35倍的加速比。即使在基准案例中使用计算节点的全部资源，Block-cells版本仍能保持50%的性能优势。Block-cells方法展现出缓解GPU架构上化学求解器计算负担的良好潜力。