Cool! I think the most critical part of this is to get a good
interface for dependence analysis. There are lots of interesting
implementations that have various time/space tradeoffs.
For example, it would be great if Omega was available as an option,
even if the compiler didn't use it by default. This argues for making
dependence analysis implementations pluggable like alias analyses.
Yes, I also thought about it that way. I think we may look at the
dependence analysis in LLVM at three levels (from the lowest to the
1) Testing for dependence given two sequences of GEP indices assuming
that base pointers are the same. The indices could have a SCEV form or
even be preprocessed to something simpler (affine expressions for example).
2) Testing for dependence of two instructions (that access memory). It
would use alias analysis to answer some queries immediately, or to check
whether two GEP base pointers equal. If the latter is the case, 1) would
be used to check for dependences.
3) Complex queries (for example: does the given loop carry dependence?).
It would use 2) and summarize its results.
Only the first level could be pluggable allowing to interchange or chain
core dependency testing techniques. I think there will be no use in
making pluggable the higher ones (please, correct me if I am wrong).
This approach would require to divide the analysis structure into two
parts, say; DependenceAnalysis and IndexingTester.
This all sounds great to me!
That said, I must admit I haven't made it that way in my prototype. I
have it in mind, but I'm currently trying to keep things simple and just
to check whether the precision of my implementation is worth anything.
I'm fine with starting simple and generalizing it out from there. I'd actually recommend against trying to implement a maximally precise dependence analyzer without a client. With no client, there is no way to test that you're getting correct results and whether the improvements in precision are actually useful.
I'd suggest starting out with a simple checker, e.g. that handles simple affine cases, and some client (a loop xform?). This should be enough to get the transformation working on simple loops, and when the client is tested and working there, you can use it to evaluate whether the precision improvements are worthwhile.
If you're looking for a simple client, I'd suggest something like loop reversal. This requires a pretty simple dependence test and can be useful for some targets. The idea is to turn:
for (i = 0 .. 100)
A[i] = 4;
for (i = 100 .. 0)
A[i] = 4;
Another transform that needs dependence analysis which would be even more useful (but still very simple) is a "loops to memset/memcpy" pass. This optimization would speed up the 'viterbi' program in the test suite a *lot* for the various 'history' loops. A simple version of this is:
for (i = 0 .. 100)
A[i] = 0;
memset(A, 0, sizeof(A)*100);
I'd suggest looking at:
Using the chains of recurrences algebra for data dependence testing
and induction variable substitution
MS Thesis, Johnie Birch
Array Data Dependence Testing with the Chains of Recurrences Algebra
An empirical evaluation of chains of recurrences for array dependence
I've read the second one, but am not sure if it's easy to implement if
overflow and unknown signedness are taken into account. For now, I will
stick to the classical Banerjee test. If time allows I'll return to the
Ok. Starting simple is good. Thanks again for working on this, this is a major hole in llvm,