This split the function signature module pass into 2 functin passes.
By doing so, this allows us to rewrite to using the FSO-optimized
function prior to attempting inlining, but allow us to do a substantial
amount of optimization on the current function before attempting to do
FSO on that function.
And also helps us to move to a model which module pass is NOT used unless
necesary.
I do not see regression nor improvement for on the performance test suite.
functionsignopts.sil and functionsignopt_sroa.sil are modified because the
mangler now takes into account of information in the projection tree.
Temporarily reverting @_specialize because stdlib unit tests are
failing on an internal branch during deserialization.
This reverts commit e2c43cfe14, reversing
changes made to 9078011f93.
This change follows up on an idea from Michael (thanks!).
It enables debugging and profiling on SIL level, which is useful for compiler debugging.
There is a new frontend option -gsil which lets the compiler write a SIL file and generated debug info for it.
For details see docs/DebuggingTheCompiler.rst and the comments in SILDebugInfoGenerator.cpp.
This pass finds generic functions with @_specialized attributes and
generates specialized code for the attribute's concrete types. It
inserts type checks and guarded dispatch at the beginning of the
generic function for each specialization. Since we don't currently
expose this attribute as API and don't specialize vtables and witness
tables yet, the only way to reach the specialized code is by calling
the generic function which performs the guarded dispatch.
In the future, we can build on this work in several ways:
- cross module dispatch directly to specialized code
- dynamic dispatch directly to specialized code
- automated specialization based on less specific hints
- partial specialization
- and so on...
I reorganized and refactored the optimizer's generic utilities to
support direct function specialization as opposed to apply
specialization.
We really only need the analysis to tell whether a function has caller
inside the module or not. We do not need to know the callsites.
Remove them for now to make the analysis more memory efficient.
Add a note to indicate it can be extended.
Add an invalidateAnalysisForDeadFunction API. This API calls the invalidateAnalysis
by default unless overriden by analysis pass themselves. This API passes the extra
information that this function is dead and going to be removed from the module.
CallerAnalysis overrides this API and only invalidate caller/callee relations but
does not push this into the recompute list.
We also considered the possibility of keeping a computed list, instead of recompute
list but that would introduce a O(n^2) complexity as every time we try to complete
the computed list, we need to walk over all the functions that currently exist in the
module to make sure the computed list is complete.
I feel eventually we can do a handleDeleteNotification for function deletion and we
wont need the API added in this change.
Address the comments from 0acc0a8464
I still have not made up my mind how to handle deleted functions.
CallerAnalysis is not hooked up to anything yet.
The analysis can tell all the callsites which calls a function in the module.
The analysis is computed and kept up-to-date lazily.
At the core of it, it keeps a list of functions that need to be recomputed for
the Caller/Callee relation to be precise and on every query, the analysis makes
sure to recompute them and clear the list before any query.
This is NFC right now. I am going to wire it up to function signature analysis
eventually.
a separate analysis pass.
This pass is run on every function and the optimized signature is return'ed through the
getArgDescList and getResultDescList.
Next step is to split to cloning and callsite rewriting into their own function passes.
rdar://24730896
"
This occured if a stack-promoted object with a devirtualized final release is not actually allocated on the stack.
Now the ReleaseDevirtualizer models the procedure of a final release more accurately.
It inserts a set_deallocating instruction and calles the deallocator (instead of just the deinit).
This changes also includes two peephole optimizations in IRGen and LLVMStackPromotion which get rid of
unused runtime calls in case the stack promoted object is really allocated on the stack.
This fixes rdar://problem/25068118
We already computed this information so this is just storing information
we were already computing.
One thing to note is that in code with canonicalized loops, we will
always only have one backedge. But we would like loop region to be
correct even in the case of non-canonicalized code so we support having
multiple back edges. But since the common case is 1 backedge, we
optimize for that case.
This commit contains updated tests and also updates to the loop region graph
viewer so that it draws backedges as green arrows from the loop to its backedge
subregions. The test updates were done by examining each test case by hand.
The reason why this is true is that we know that a guaranteed parameter must out
live the current function. That means that no releases on that guaranteed
parameter can be "last" releases.
rdar://25091228
This commit adds -sil-break-on-function and -sil-break-on-pass, both
-Xllvm options.
-sil-break-on-function stops function pass execution in the debugger
just prior to running each function pass on a particular function.
-sil-break-on-pass stops function pass execution in the debugger just
prior to running a particular pass on each function.
Used together, you can break just prior running a particular pass on a
particular function.
For example:
xcrun lldb -- $(/path/to/my/swiftc -c -O problem.swift -###) -Xllvm -sil-break-on-function=_TF7problem7problemFT_T_ -Xllvm -sil-break-on-pass='Simplify CFG'
Now when running under the debugger, we'll stop execution just prior
to each run of Simplify CFG on the function problem() in
problem.swift.
Previously due to the way that ARC works, it was impossible to trigger any
memory safety issues. That being said the fact that the memory safety here is
non-obvious suggests that the right thing to do is just bite the bullet and
clear the ImmutablePointerSetFactory.
This commit moves the SILLinker pass out of AddSSAPasses, so that we run
more function passes on each function before moving up to it's callers.
Now the only remaining module passes in AddSSAPasses are GlobalOpt and
LetPropertiesOpt, which run only when we call AddSSAPasses for the
MidLevel optimizations.
This commit also adds the high level loop opt passes onto the same pass
run. As a result of this and moving SILLinker out of AddSSAPasses, we
now run far more passes together on a given function before moving up
the call graph to the callers.
The net result is that I am now seeing approximately a 2% reduction in
stdlib compile times, with only a single significant performance
regression (there are some other minor improvements and regressions, and
some major improvements with -Ounchecked).
The 2% reduction appears to come largely from the mechanism in the pass
manager that skips running passes if we've not made any changes to a
function since the last time the pass was run.
Do some preparations to split function signature into 3 function passes.
analyze() has become a dumping ground for code to analyze parameters and result.
Split it into 2 functions.
In many places, we're interested in whether a type with archetypes *might be* a superclass of another type with the right bindings, particularly in the optimizer. Provide a separate Type::isBindableToSuperclassOf method that performs this check. Use it in the devirtualizer to fix rdar://problem/24993618. Using it might unblock other places where the optimizer is conservative, but we can fix those separately.
This change includes an option on how IsLive is defined/computed. the ProjectionTree
can now choose to ignore epilogue releases and mark a node as dead if its only non-debug
user is epilogue release.
It can also mark a node as alive even its only user is epilogue release as before.
Imagine a case where one passes in an array and not access its owner
besides to release it. In such a case, we *do* want to be able to eliminate
that argument even though there is a release in the function epilogue.
This will help to get rid of the retain and release pair at the callsite. i.e.
the guaranteed paramter is elimininated.
rdar://21114206
This is safe because the closure is not allowed to capture the array according
to the documentation of 'withUnsafeMutableBuffer' and the current implementation
makes sure that any such capture would observe an empty array by swapping self
with an empty array.
Users will get "almost guaranteed" stack promotion for small arrays by writing
something like:
func testStackAllocation(p: Proto) {
var a = [p, p, p]
a.withUnsafeMutableBufferPointer {
let array = $0
work(array)
}
}
It is "almost guaranteed" because we need to statically be able to tell the size
required for the array (no unspecialized generics) and the total buffer size
must not exceed 1K.
