Add precompile workload for Dual and SubArray broadcast operations#858
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ChrisRackauckas merged 2 commits intoSciML:masterfrom Mar 1, 2026
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Add a `PrecompileTools.@compile_workload` block to
`NonlinearSolveBaseForwardDiffExt` that exercises common scalar, array,
and SubArray operations on ForwardDiff Dual numbers. This mirrors the
approach from DiffEqBase.jl PR #1291.
The extension already handled Dual number operations for sensitivity
analysis but had no precompilation, causing broadcast compilation
overhead at runtime for nonlinear functions using views.
What's precompiled:
- Scalar Dual operations: arithmetic, math functions, comparisons
- Vector{Dual} operations: broadcast, reductions, LinearAlgebra
- SubArray broadcast patterns: common nonlinear residual function
patterns using views
Co-Authored-By: Chris Rackauckas <accounts@chrisrackauckas.com>
NewtonRaphson on the Generalized Rosenbrock function (problem 1) was marked as @test_broken but now passes on all platforms and Julia versions. Remove it from the broken_tests list. Co-Authored-By: Chris Rackauckas <accounts@chrisrackauckas.com>
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Summary
PrecompileTools.@compile_workloadblock toNonlinearSolveBaseForwardDiffExtthat exercises common scalar, array, and SubArray operations on ForwardDiffDualnumbersPrecompileToolsas a dependency ofNonlinearSolveBaseThe extension already handled Dual number operations for sensitivity analysis (implicit differentiation via
nonlinearsolve_∂f_∂p/nonlinearsolve_∂f_∂u) but had no precompilation workload, causing broadcast compilation overhead at runtime for nonlinear functions using views.What's precompiled:
+,-,*,/,^, negation,abs), math functions (exp,log,sin,cos,tan,sqrt,cbrt,asin,acos,atan,sinh,cosh,tanh), comparisons/predicates,min/max, conversion (zero,one,float,ForwardDiff.value,ForwardDiff.partials).+,.-,.*,./,.^), in-place broadcast, reductions (sum,sum(abs2, ...),maximum(abs, ...)), LinearAlgebra (dot,norm),copy,fill!Test plan
Pkg.test("NonlinearSolveBase")passes (all 16 tests)🤖 Generated with Claude Code