pith:7FT3R4XQ
Hierarchical Transformer Preconditioning for Interactive Physics Simulation
A hierarchical transformer preconditioner solves stiff multiphase Poisson systems up to 28 times faster than standard GPU incomplete factorization.
arxiv:2605.13343 v2 · 2026-05-13 · cs.GR · cs.DC · cs.LG · cs.NA · math.NA
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On stiff multiphase Poisson systems (up to 100:1 density contrast, N = 1,024-16,384), the solver runs from ~143 to ~21 fps. At N = 8,192, it reaches 17.9 ms/frame, with 2.2x speedup over GPU Jacobi, ~28x over GPU IC/DILU (AMGX multicolor_dilu), and 2.7x over neural SPAI retrained per scale on the same benchmark.
The weak-admissibility H-matrix partition plus highway connections in the transformer are assumed to capture long-range couplings sufficiently for the cosine-Hutchinson objective to produce a preconditioner that improves PCG convergence on irregular spectra without post-hoc tuning.
A hierarchical transformer preconditioner with H-matrix structure and cosine-Hutchinson training delivers up to 2.7x speedup over prior neural methods on stiff multiphase Poisson systems up to N=16384.
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| First computed | 2026-05-18T02:44:48.366686Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
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| jq -c '.canonical_record' \
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Canonical record JSON
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