forked from 1b-agent/fieldcraft-upstream
Deterministic CPU multithreading: supernodal Cholesky, parallel elements, LBM blocks (#50)
* parallel: deterministic thread pool helpers for the solvers (fixed partitions, ordered results) Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01NmAttHhUZTokgPeEJia8sm * solver: supernodal left-looking Cholesky, multithreaded with a fixed operation order Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01NmAttHhUZTokgPeEJia8sm * solver: parallel element matrices, stresses, Lanczos block solves and products (sums in the sequential order) Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01NmAttHhUZTokgPeEJia8sm * explicit: element updates in parallel, nodal forces added in element order (bit-identical to the sequential loop) Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01NmAttHhUZTokgPeEJia8sm * lbm: collision and streaming by fixed cell blocks in parallel, wall forces in link order (bit-identical) Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01NmAttHhUZTokgPeEJia8sm * engine: threads setting for the solve commands (session default from MODELCRAFT_THREADS or the cores); bit-identity test on 1, 2 and 7 threads Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01NmAttHhUZTokgPeEJia8sm * docs: rayon threads in ADR 0001, the parallel crate, supernodal Cholesky Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01NmAttHhUZTokgPeEJia8sm --------- Co-authored-by: jyviko <2501648+jyviko@users.noreply.github.com> Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
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//! von Mises. Frequency analysis ([`eigen`]) runs shift-invert block Lanczos on the same
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//! kind of factorization.
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//!
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//! Everything is sequential and in a fixed order, so the same model gives the same numbers bit
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//! for bit; sizes and iterations are capped by [`Limits`].
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//! Element matrices and stresses, the factorization's subtrees and dense tiles, the Lanczos
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//! block solves and matrix products run on threads ([`modelcraft_parallel`]), but every number
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//! is computed by one task in an order fixed by the model alone and sums are taken in a fixed
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//! order, so the same model gives the same numbers bit for bit on any number of threads and on
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//! every platform; sizes and iterations are capped by [`Limits`].
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#![deny(clippy::unwrap_used, clippy::expect_used, clippy::panic, clippy::unimplemented, clippy::todo, clippy::unreachable)]
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#![forbid(unsafe_code)]
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// Matrix kernels read as the textbook formulas with index loops.
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