PerturbedEquilibrium: reduce allocations and parallelize the singular-coupling loop#325
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PerturbedEquilibrium: reduce allocations and parallelize the singular-coupling loop#325logan-nc wants to merge 2 commits into
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The per-surface field reconstruction allocated heavily on every surface and ran multi-threaded BLAS inside its Julia @threads loops. Cut the allocation and remove the oversubscription, with bit-identical results: - Run the R,Z,phi mode DFTs in place (inverse_transform!/transform! into per-thread buffers) instead of the allocating inverse()/ft() functors. - @view the mpert x mpert eigenmode-matrix slices in sum_eigenmode_contributions (mul! takes the view; no per-surface copy). - cholesky! in place on the per-thread scratch matrix in the clebsch solve. - Pin BLAS to one thread across reconstruct_physical_fields (save/restore): the per-surface BLAS kernels are small, so multi-threaded BLAS oversubscribes the cores against the Julia @threads over psi. Effect on the DIII-D reference case: PerturbedEquilibrium allocations drop ~30% (594 -> 420 MB), GC time falls, and the b_n / xi_n spectra, resonant coupling matrices, and resonant vectors are bit-identical before and after and independent of thread count. This is a memory/allocation cleanup: it does NOT materially change PE wall time, which on this case is dominated by the (serial) singular-coupling metrics and the response-matrix linear algebra rather than the threaded reconstruction.
…ional surfaces The singular-coupling metrics loop over rational surfaces was serial, and it is the largest PerturbedEquilibrium phase because each surface builds its own vacuum Green's functions (an allocation-local `compute_vacuum_response`). The surfaces are independent -- each writes disjoint coupling-matrix rows and its own `sing[s]` entry -- so thread the loop (`@threads :static` over resonant pairs), with BLAS pinned to one thread across it (each surface's solve is small; multi-threaded BLAS would oversubscribe against the Julia threads). Effect on the DIII-D reference case: the singular-coupling phase drops from ~0.54 s to ~0.18 s at 8 threads (~3x), cutting the PerturbedEquilibrium wall time from ~0.94 s to ~0.59 s. Results are unchanged: the resonant coupling matrices and applied resonant vectors are identical across thread counts (deterministic, no data race) and agree with the serial result to ~13-15 significant figures (floating-point reordering from the BLAS pinning); the coordinate-invariance, coils, full-run, and HDF5-replay regression suites pass.
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PerturbedEquilibrium: reduce allocations and parallelize the singular-coupling loop
Two independent PerturbedEquilibrium performance improvements on the DIII-D-like reference
case, both verified to leave results unchanged (bit-identical / within regression tolerance,
and thread-count-independent).
1. Parallelize the singular-coupling loop over rational surfaces (the real speedup)
The singular-coupling metrics loop (
SingularCoupling.jl) was serial, and it was thelargest PE phase: each rational surface builds its own vacuum Green's functions (an
allocation-local
compute_vacuum_response). The surfaces are independent -- each writesdisjoint coupling-matrix rows and its own
sing[s]entry -- so the loop is now threaded(
@threads :staticover resonant pairs), with BLAS pinned to one thread across it (eachsurface's solve is small; multi-threaded BLAS would oversubscribe the cores against the
Julia threads).
~0.94 s to ~0.59 s. (Field reconstruction, which is memory-bandwidth-bound, is now the
dominant PE phase.)
serial result to ~13-15 significant figures (floating-point reordering from the BLAS pin).
2. Reduce allocations in field reconstruction (a memory cleanup)
reconstruct_physical_fieldsallocated heavily per flux surface and ran multi-threaded BLASinside its
@threadsloops. Trimmed with bit-identical results:inverse_transform!/transform!into per-thread buffers)instead of the allocating
inverse()/ft()functors.@viewthempert x mperteigenmode-matrix slices insum_eigenmode_contributions.cholesky!in place on the per-thread scratch matrix in the clebsch solve.reconstruct_physical_fields.Effect: PE allocations drop ~30% (594 -> 420 MB), GC time falls, outputs bit-identical.
This is a memory cleanup, not a wall-time win on this case -- reconstruction is
bandwidth-bound, not GC-bound.
Verification
b_n/xi_nspectra,C_resonant_*coupling matrices,
resonant_*vectors): identical across thread counts and matching theserial baseline to all-but-the-last-digit.
transforms).