Performance improvements: Add @inbounds optimization for ~43% RHS speedup #30
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This PR improves the performance of the RHS evaluation by adding @inbounds annotations to the generated code loops. This eliminates bounds checking overhead in the hot paths. ## Performance Improvements **RHS Evaluation Benchmark (Telegraph model, 2x21x81 state space):** - Before: ~101μs per call - After: ~58μs per call - **Speedup: ~43%** ## Changes ### Performance Optimizations - Add @inbounds to singleindices loop in build_rhs_firstpass - Add @inbounds to pairedindices loops in build_rhs_secondpass - Add @inbounds to steady-state RHS single pass loop - Add @inbounds to sparse matrix construction loops ### Testing - Add allocation tests to verify RHS evaluation remains allocation-free - Add tests for singleindices and pairedindices iteration - Add allocation test for the 3-species Telegraph model The @inbounds optimization is safe because: 1. singleindices returns CartesianIndices which are guaranteed valid 2. pairedindices returns index pairs that are computed to be within bounds 3. The index handlers ensure all generated indices are valid 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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Summary
@inboundsannotations to generated RHS code loops for ~43% speedupPerformance Benchmarks
RHS Evaluation (Telegraph model, 2x21x81 state space):
Index Iteration:
singleindices: 0 allocationspairedindices: 0 allocationsChanges
src/build_rhs.jl@inboundsto the first pass loop (singleindices iteration)@inboundsto the second pass loops (pairedindices iteration)src/build_rhs_ss.jl@inboundsto the steady-state single pass loopsrc/matrix.jl@inboundsto sparse matrix construction loopstest/alloc_tests.jl(new)The
@inboundsoptimization is safe because:singleindicesreturnsCartesianIndiceswhich are guaranteed validpairedindicesreturns index pairs computed to be within boundsTest Plan
cc @ChrisRackauckas
🤖 Generated with Claude Code