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This patch adds foldl' to GhcPrelude and changes must occurences
of foldl to foldl'. This leads to better performance especially
for quick builds where GHC does not perform strictness analysis.
It does change strictness behaviour when we use foldl' to turn
a argument list into function applications. But this is only a
drawback if code looks ONLY at the last argument but not at the first.
And as the benchmarks show leads to fewer allocations in practice
at O2.
Compiler performance for Nofib:
O2 Allocations:
-1 s.d. ----- -0.0%
+1 s.d. ----- -0.0%
Average ----- -0.0%
O2 Compile Time:
-1 s.d. ----- -2.8%
+1 s.d. ----- +1.3%
Average ----- -0.8%
O0 Allocations:
-1 s.d. ----- -0.2%
+1 s.d. ----- -0.1%
Average ----- -0.2%
Test Plan: ci
Reviewers: goldfire, bgamari, simonmar, tdammers, monoidal
Reviewed By: bgamari, monoidal
Subscribers: tdammers, rwbarton, thomie, carter
Differential Revision: https://phabricator.haskell.org/D4929
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the hot path contained a call to
v `elemUnVarSet` (neighbors g v)
and creating the set of neighbors just to check if `v` is inside
accounted for half the allocations of the test case of #15164.
By introducing a non-allocating function `hasLoopAt` for this we shave
off half the allocations. This brings the total cost of Call Arity down
to 20% of time and 23% of allocations, according to a profiled run. Not
amazing, but still much better.
Differential Revision: https://phabricator.haskell.org/D4718
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This switches the compiler/ component to get compiled with
-XNoImplicitPrelude and a `import GhcPrelude` is inserted in all
modules.
This is motivated by the upcoming "Prelude" re-export of
`Semigroup((<>))` which would cause lots of name clashes in every
modulewhich imports also `Outputable`
Reviewers: austin, goldfire, bgamari, alanz, simonmar
Reviewed By: bgamari
Subscribers: goldfire, rwbarton, thomie, mpickering, bgamari
Differential Revision: https://phabricator.haskell.org/D3989
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This patch improves the call arity analysis in various ways.
Most importantly, it enriches the analysis result information so that
when looking at a call, we do not have to make a random choice about
what side we want to take the information from. Instead we can combine
the results in a way that does not lose valuable information.
To do so, besides the incoming arities, we store remember "what can be
called with what", i.e. an undirected graph between the (interesting)
free variables of an expression. Of course it makes combining the
results a bit more tricky (especially mutual recursion), but still
doable.
The actually implemation of the graph structure is abstractly put away
in a module of its own (UnVarGraph.hs)
The implementation is geared towards efficiently representing the graphs
that we need (which can contain large complete and large complete
bipartite graphs, which would be huge in other representations). If
someone feels like designing data structures: There is surely some
speed-up to be obtained by improving that data structure.
Additionally, the analysis now takes into account that if a RHS stays a
thunk, then its calls happen only once, even if the variables the RHS is
bound to is evaluated multiple times, or is part of a recursive group.
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