When checking for false positives, we want to make sure that if a
debug_value is dropped, we also find a real instruction that shares
the same scope as the debug_value or has a scope that is a child
of the scope of the debug_value, and has an inlinedAt equal to the
inlinedAt of the debug_value or it's inlinedAt chain contains the
inlinedAt of the debug_value. However, this instruction shouldn't be
another debug_value.
The check was supossed to check if(!I.isDebugInstruction())
but it checked if(I.isDebugInstruction())
This patch fixes that bug.
This patch adds false positive detection to sil-stats-lost-variables.
We will now only detect a debug_value as lost if there is a real
instruction which belongs to the same scope or a child scope of the
scope of the debug_value and if they are both inline at the same
location.
//a
Although I don't plan to bring over new assertions wholesale
into the current qualification branch, it's entirely possible
that various minor changes in main will use the new assertions;
having this basic support in the release branch will simplify that.
(This is why I'm adding the includes as a separate pass from
rewriting the individual assertions)
getVarInfo() now always returns a variable with a location and scope.
To opt out of this change, getVarInfo(false) returns an incomplete variable.
This can be used to work around bugs, but should only really be used for
printing.
The complete var info will also contain the type, except for debug_values,
as its type depends on another instruction, which may be inconsistent if
called mid-pass.
All locations in debug variables are now also stripped of flags, to avoid
issues when comparing or hashing debug variables.
Now that we've moved to C++14, we no longer need the llvm::make_unique
implementation from STLExtras.h. This patch is a mechanical replacement
of (hopefully) all the llvm::make_unique instances in the swift repo.
This name makes it clear that the function has not yet been deleted and also
contrasts with the past tense used in the API notifyAddedOrModifiedFunction to
show that said function has already added/modified the function.
The name notifyAddFunction is actively harmful since the pass manager uses this
entrypoint to notify analyses of added *OR* modified functions. It is up to the
caller analysis to distinguish in between these cases.
I am not vouching for the design, just trying to make names match the
current behavior.
Generally in the SIL/SILOptimizer libraries we have been putting kinds in the
swift namespace, not a nested scope in a type in swift (see ValueKind as an
example of this).
introduce a common superclass, SILNode.
This is in preparation for allowing instructions to have multiple
results. It is also a somewhat more elegant representation for
instructions that have zero results. Instructions that are known
to have exactly one result inherit from a class, SingleValueInstruction,
that subclasses both ValueBase and SILInstruction. Some care must be
taken when working with SILNode pointers and testing for equality;
please see the comment on SILNode for more information.
A number of SIL passes needed to be updated in order to handle this
new distinction between SIL values and SIL instructions.
Note that the SIL parser is now stricter about not trying to assign
a result value from an instruction (like 'return' or 'strong_retain')
that does not produce any.
This patch implements collection and dumping of statistics about SILModules, SILFunctions and memory consumption during the execution of SIL optimization pipelines.
The following statistics can be collected:
* For SILFunctions: the number of SIL basic blocks, the number of SIL instructions, the number of SIL instructions of a specific kind, duration of a pass
* For SILModules: the number of SIL basic blocks, the number of SIL instructions, the number of SIL instructions of a specific kind, the number of SILFunctions, the amount of memory used by the compiler, duration of a pass
By default, any collection of statistics is disabled to avoid affecting compile times.
One can enable the collection of statistics and dumping of these statistics for the whole SILModule and/or for SILFunctions.
To reduce the amount of produced data, one can set thresholds in such a way that changes in the statistics are only reported if the delta between the old and the new values are at least X%. The deltas are computed as using the following formula:
Delta = (NewValue - OldValue) / OldValue
Thresholds provide a simple way to perform a simple filtering of the collected statistics during the compilation. But if there is a need for a more complex analysis of collected data (e.g. aggregation by a pipeline stage or by the type of a transformation), it is often better to dump as much data as possible into a file using e.g. -sil-stats-dump-all -sil-stats-modules -sil-stats-functions and then e.g. use the helper scripts to store the collected data into a database and then perform complex queries on it. Many kinds of analysis can be then formulated pretty easily as SQL queries.
