Radiation schemes are fundamental components of weather and climate models that need to be both efficient and accurate. In this work we refactor ecRad, a flexible radiation scheme developed at the European Centre for Medium-Range Weather Forecasts (ECMWF). The goal was to improve performance especially with ecCKD, a new gas optics scheme that requires only 32 spectral intervals in the longwave and shortwave to be accurate. This speeds up ecRad considerably, but also reduces performance due to short inner loops.
We therefore carry out both higher-level code restructuring and kernel-level optimizations for the radiative transfer solvers TripleClouds and SPARTACUS. SPARTACUS computes cloud 3D radiative effects, which have so far been neglected in large-scale models. We exploit the lack of vertical loop dependencies in key computations by merging the spectral and vertical dimensions, improving vectorization and instruction-level parallelism.
On the new AMD Rome-based ECMWF supercomputer, we obtain a 3-fold speedup for both solvers when using 32-term ecCKD models. Combining ecCKD with optimized code results in very fast yet accurate radiation computations: with TripleClouds we achieve 1.7 TFLOPs and a throughput of 621 columns/ms on a 128-core node. This is 11.5 times faster than ecRad in Integrated Forecasting System cycle 47r3, which uses a more noisy solver (McICA) and less accurate gas optics (RRTMG). SPARTACUS with ecCKD is now 2.4 times faster than CY47r3-ecRad, making cloud 3D radiative effects affordable to compute within large-scale models. Preliminary results show that SPARTACUS slightly improves forecasts of 2-metre temperature and low clouds in the tropics.