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@rchen20 rchen20 commented Dec 16, 2025

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Most Sn transport codes are designed around one of these nestings, which is an inflexibility that leads to software engineering compromises when porting to new architectures and programming paradigms.

Early research has found that the problem dimensions (zones, groups, directions, scattering order) and the scaling (number of threads and MPI tasks), can make a profound difference in the performance of each of these nestings.
To our knowledge, this is a capability unique to Kripke, and should provide key insight into how data-layout affects Sn solver performance.
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@rchen20 We need details in the code modification section on what may be changed, and what should stay the same. If I am not mistaken, the data ordering (GDZ) needs to stay the same,. while the execution policy can be changed and optimizations like loop tiling are allowed.

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