RecomputeFunctionList should really be a SmallVector instead of a
DenseSet. A DenseSet gives rise to a nondeterminstic way of iterating over
all functions.
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
"
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
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.
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.
LSValue::reduce reduces a set of LSValues (mapped to a set of LSLocations) to
a single LSValue.
It can then be used as the forwarding value for the location.
Previously, we expand into intermediate nodes and leaf nodes and then go bottom
up, trying to create a single LSValue out of the given LSValues.
Instead, we now use a recursion to go top down. This simplifies the code. And this
is fine as we do not expect to run into type tree that are too deep.
Existing test cases ensure correctness.
This enables function signature handles a case of self-recursion.
With this change we convert 11 @owned return value to "not owned", while
we convert 179 @owned parameter to @guanrateed.
rdar://24022375
More specifically, this handles a case of self-recursion.
With this change we convert 11 @owned return value to "not owned", while
we convert 179 @owned parameter to @guanrateed.
rdar://24022375
Reinstates commit 0c2ca94ef7
With two bug fixes:
*) use after free asan crash
*) wrong check in ValueLifetimeAnalysis::isWithinLifetime
And some refactoring
We were giving special handling to ApplyInst when we were attempting to use
getMemoryBehavior(). This commit changes the special handling to work on all
full apply sites instead of just AI. Additionally, we look through partial
applies and thin to thick functions.
I also added a dumper called BasicInstructionPropertyDumper that just dumps the
results of SILInstruction::get{Memory,Releasing}Behavior() for all instructions
in order to verify this behavior.
With this re-abstraction a specialized function has the same calling convention as if it would have been written with the specialized types in the first place.
In general this results in less alloc_stacks and load/stores.
It also can eliminate some re-abstraction thunks, e.g. if a generic closure is used in a non-generic context.
It some (hopefully rare) cases it may require to add re-abstraction thunks.
In case a function has multiple indirect results, only the first is converted to a direct result. This is an open TODO.
Currently the array.get_element calls return the element as indirect result.
The generic specializer will change so that the element can be returned as direct result.
For a release on a guaranteed function paramater, we know right away
that its not the final release and therefore does not call deinit.
Therefore we know it does not read or write memory other than the reference
count.
This reduces the compilation time of dead store and redundant load elim. As
we need to go over alias analysis to make sure tracked locations do not alias
with it.
