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Replace expensive second babel-traverse pass with fast custom visitor. #1947
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Release notes: Speeding up Prepack by 22%, saving 8% memory. This closes #1812. This completely refactors the `ClosureRefReplacer` into a new standalone `ResidualFunctionInstantiator`. By avoiding babel-traverse, this visitor implementation is way faster. Also, it only clones those nodes which are being changed, preserving all others, insteading of cloning an entire function just in case any node needs to change; in this way, memory is saved as well. On a large internal benchmark, this change reduces overall time from 200s down to 157s: 22% faster. This due to the time savings during serialization, which goes down from 71s to 23s (while making the visitor 6s slower due to additional work). Also, overall memory usage goes down from 3582MB to 3307MB, a 8% savings. Again, mostly due to savings in serialization, with surviving allocations going down from 337MB to 51MB, while slightly increasing allocations in the visitor by 11MB as it has to store additional data.
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I know @loganfsmyth and @hzoo might be super busy, but if they could take a look at some of the Babel related code here it might be good to see if there are any further optimizations that we might be able to do to improve performance. |
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Release notes: Speeding up Prepack by 22%, saving 8% memory.
This closes #1812.
This completely refactors the
ClosureRefReplacerinto a newstandalone
ResidualFunctionInstantiator.By avoiding babel-traverse, this visitor implementation is way faster.
Also, it only clones those nodes which are being changes, preserving all others,
insteading of cloning an entire function if any node needs to change; in this way,
memory is saved as well.
On a large internal benchmark (27MB minified JavaScript bundle with 31MB sourcemaps file), this change reduces overall time from 200s down to 157s: 22% faster. This due to savings during serialization, which goes down from 71s to 23s (while making the visitor 6s slower due to additional work).
Also, overall memory usage goes down from 3582MB to 3307MB, a 8% savings. Again, mostly due to savings in serialization, where surviving allocations going down from 337MB to 51MB, while slightly increasing allocations in the visitor.