Aiken UPLC Optimization overhaul #1052
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MicroProofs
changed the title
…e swept up by the builtin force reduction
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Slight regression with some fold functions. Going to look into that tomorrow. Overall some improvements though. |
… forward pass being able to apply an argument that may have no_inline at the top where as vice-versa would reduce the arg first.
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Much better |
KtorZ
reviewed
Nov 13, 2024
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| loop { | ||
| let (current_program, context) = prog.multi_pass(); | ||
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| if context.node_count == prev_count { | ||
| prog = current_program; | ||
| break; | ||
| } else { | ||
| prog = current_program; | ||
| prev_count = context.node_count; | ||
| } | ||
| } |
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Is this guaranteed to always converge to a fixed point though? I could imagine infinite cycles with an optimization pass adding some nodes, and the next one removing them. So we might need to track not the previous count, but the min(all previous counts).
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Refactor and structure optimizations to be less computationally heavy.
So instead of one pass one optimization. We finally do one pass several optimizations. There are still some optimizations that need an independent pass like the curry optimization since it actually does 2 passes. We also separate out optimizations that only need a single pass.
Now to make sure we beat all the benchmarks.