(transform): convert to csl_stencil.apply #2803
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Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## main #2803 +/- ##
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+ Coverage 89.79% 89.84% +0.04%
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Files 394 397 +3
Lines 48747 49342 +595
Branches 7471 7592 +121
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+ Hits 43774 44332 +558
- Misses 3793 3815 +22
- Partials 1180 1195 +15 ☔ View full report in Codecov by Sentry. |
AntonLydike
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Jul 2, 2024
AntonLydike
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Jul 2, 2024
dk949
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Jul 2, 2024
Co-authored-by: Anton Lydike <[email protected]>
AntonLydike
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Jul 4, 2024
n-io
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Jul 26, 2024
Adds a canonicalisation pass for `csl_stencil.apply`. The op takes an empty tensor as`iter_arg`, which it does not manage itself. The conversion pass in #2803 initialises an `iter_arg` for each instance of `apply`. This canonicalisation pass identifies where this can be re-used, effectively removing redundant allocations. --------- Co-authored-by: n-io <[email protected]>
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This PR implements the conversion to csl_stencil.apply op as outlined in Step 2 of #2747
The
csl_stencil.applyop combines a csl_stencil.prefetch (symmetric buffer communication across a given stencil shape) with a stencil.apply.The transformation consists of several steps:
stencil.apply, select thecsl_stencil.prefetchwith the biggest memory overhead (if several are present) to be fused with the apply op into acsl_stencil.apply(a+b)+c -> (c+a)+bto access, consume, and reduce data of neighbours (for input stencil only)tensor.InsertSliceOpto insert computed chunk into returned z-value tensor