Fix diffusion dask OOM: pass scalar diffusivity directly to chunks#1117
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brendancol merged 4 commits intomasterfrom Mar 31, 2026
Merged
Fix diffusion dask OOM: pass scalar diffusivity directly to chunks#1117brendancol merged 4 commits intomasterfrom
brendancol merged 4 commits intomasterfrom
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Parallel subagent triage + ralph-loop workflow for auditing all xrspatial modules for performance bottlenecks, OOM risk under 30TB dask workloads, and backend-specific anti-patterns.
7 tasks covering command scaffold, module scoring, parallel subagent dispatch, report merging, ralph-loop generation, and smoke tests.
For scalar diffusivity, the dask chunk function now receives the float value directly instead of a full-raster numpy array captured in every task closure. This eliminates the O(H*W) eager allocation and the per-task serialization overhead. For DataArray diffusivity, the dask path passes the dask array as a second argument to map_overlap so each chunk gets only its own slice.
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Summary
map_overlapso each chunk gets only its own slicenp.full(agg.shape, ...)allocation (line 261) anddiffusivity.valuesmaterialization (line 255) that caused OOM on large dask inputsContext
Found during performance sweep triage (#1116). On 512x512: dask used 35 MB vs numpy's 27 MB, with the 8 MB gap from the full-raster alpha_arr. At 30TB this allocation alone would OOM before any diffusion work starts.
Test plan
test_dask_matches_numpyconfirms dask scalar path matches numpy output