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simplify mapreduce_impl #16217

Merged
merged 1 commit into from
Jun 3, 2016
Merged

simplify mapreduce_impl #16217

merged 1 commit into from
Jun 3, 2016

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vtjnash
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@vtjnash vtjnash commented May 5, 2016

this is largely now possible since Functors are not needed for performance
fixes #16185

@KristofferC
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I don't think we should close #16185 until the reduced example I posted there is fixed. Alternatively a new issue could be made for that example.

@JeffBezanson
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The reduced example in that issue might not get fixed. The extra code allows dynamic dispatch to a version of g specialized for f. The method in the example is probably not performance-critical, since all it does is call another function. This is part of the cost of faster higher-order functions.

@StefanKarpinski
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From triage call:

@StefanKarpinski
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TODO: there should be a note in NEWS about the changed reduction order.

@JeffBezanson
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We should definitely keep both pairwise summation and the 0.4 level of performance. If necessary we should manually specialize sum, or use a reduce_impl that has the mapping function removed.

this is possible now that Functors are not needed for performance
fixes #16185
@vtjnash vtjnash merged commit b0bc3f7 into master Jun 3, 2016
@vtjnash vtjnash deleted the jn/mapreduce-fast-again branch June 3, 2016 03:54
@tkelman
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tkelman commented Jun 4, 2016

Apparently DataArrays was using sum_pairwise_blocksize

@vtjnash
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vtjnash commented Jun 4, 2016

it can define sum_pairwise_blocksize(T) = pairwise_blocksize(T, +) for compatibility

@nalimilan
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That's what I did in JuliaStats/DataArrays.jl#192. If that was the only use of it outside of Base, I guess that's OK.

@tkelman
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tkelman commented Jun 5, 2016

NullableArrays was also using it.

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performance regression in sum(a)
6 participants