enumerate them lazily.
This leads to compilation time improvement, as some of the LSValues previously
enumerated do not be created in this approach.
i.e. we enumerate LSValues created by loads previously, but the LoadInsts could be
target for RLE. In such case, the enumerated LSValues are not used.
Compilation time improvement: 1775ms to 1721ms (2.7% to 2.6% of the entire
compilation time for stdlib -O).
Existing tests ensure correctness.
Note: we still enumerate locations, as we need to know how many locations there are
in the function to resize the bitvector appropriately before the data flow runs.
1. Update some comments.
2. Rename a few functions, e.g. runIterativeDF -> runIterativeRLE, getLSValueBit -> getValueBit.
3. Remove unused headers.
4. Remove no-longer used function, mergePredecessorStates and mergePredecessorState.
5. A few other small NFCs.
Previously we process every instruction every time the data flow re-iterates.
This is very inefficient.
In addition to moving to genset and killset, we also group function into
OneIterationFunction which we know that the data flow would converge in 1 iteration
and functions that requre the iterative data flow, mostly due to backedges in loops.
we process them differently.
I observed that there are ~93% of the functions that require just a single iteration
to perform the RLE.
But the other 7% accounts for 2321 (out of 6318) of the redundant loads we eliminated.
This change reduces RLE compilation from 4.1% to 2.7% of the entire compilation time
(frontend+OPT+LLVM) on stdlib with -O. This represents 6.9% of the time spent
in SILOptimizations (38.8%).
~2 weeks ago, RLE was taking 1.9% of the entire compilation time. It rose to 4.1%
mostly due to that we are now eliminating many more redundant loads (mostly thank
to Erik's integragtion of escape analysis in alias analysis). i.e. 3945 redundant
loads elimnated before Erik's change to 6318 redundant loads eliminated now.
After the refactoring, RLE runs in the following phases:
Phase 1. we use an iterative data flow to compute whether there is an
available value at a given point, we do not yet care about what the value
is.
Phase 2. we compute the real forwardable value at a given point.
Phase 3. we setup the SILValues for the redundant load elimination.
Phase 4. we perform the redundant load elimination.
Previously we were computing available bit as well as what the available
value is every iteration of the data flow.
I do not see a compilation time improvement though, but this helps to move
to a genset and killset later as we only need to expand Phase 1 into a few smaller
phases to compute genset & killset first and then iterate until convergence for
the data flow.
I verified that we are performing same # of RLE on stdlib before the change.
Existing test ensure correctness.
i.e. multiple different values from predecessors
Previously, RLE is placing the SILArguments and branch edgevalues itself. This is probably
not as reliable/robust as using the SSAupdater.
RLE uses a single SSAupdater to create the SILArguments, this way previously created SILArguments
can be reused.
One test is created specifically for that so that we do not generate extraneous SILArguments.
RLE is an iterative data flow. Functions with too many locations may take a long time for the
data flow to converge.
Once we move to a genset and killset for RLE. we should be able to lessen the condition a bit more.
I have observed no difference in # of redundant loads eliminated on the stdlib (currently we
eliminate 3862 redundant loads).
i.e. multiple different values from predecessors
Previously, RLE is placing the SILArguments and branch edgevalues itself. This is probably
not as reliable/robust as using the SSAupdater.
RLE uses a single SSAupdater to create the SILArguments, this way previously created SILArguments
can be reused.
One test is created specifically for that so that we do not generate extraneous SILArguments.
(libraries now)
It has been generally agreed that we need to do this reorg, and now
seems like the perfect time. Some major pass reorganization is in the
works.
This does not have to be the final word on the matter. The consensus
among those working on the code is that it's much better than what we
had and a better starting point for future bike shedding.
Note that the previous organization was designed to allow separate
analysis and optimization libraries. It turns out this is an
artificial distinction and not an important goal.
