- Nov 13, 2011
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Chandler Carruth authored
when we fail to place all the blocks of a loop. Currently this is happening for unnatural loops, and this logic helps more immediately point to the problem. llvm-svn: 144504
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Chandler Carruth authored
branches that also may involve fallthrough. In the case of blocks with no fallthrough, we can still re-order the blocks profitably. For example instruction decoding will in some cases continue past an indirect jump, making laying out its most likely successor there profitable. Note, no test case. I don't know how to write a test case that exercises this logic, but it matches the described desired semantics in discussions with Jakob and others. If anyone has a nice example of IR that will trigger this, that would be lovely. Also note, there are still assertion failures in real world code with this. I'm digging into those next, now that I know this isn't the cause. llvm-svn: 144499
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Chandler Carruth authored
llvm-svn: 144498
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Chandler Carruth authored
llvm-svn: 144497
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Chandler Carruth authored
llvm-svn: 144496
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Chandler Carruth authored
second algorithm, but only loosely. It is more heavily based on the last discussion I had with Andy. It continues to walk from the inner-most loop outward, but there is a key difference. With this algorithm we ensure that as we visit each loop, the entire loop is merged into a single chain. At the end, the entire function is treated as a "loop", and merged into a single chain. This chain forms the desired sequence of blocks within the function. Switching to a single algorithm removes my biggest problem with the previous approaches -- they had different behavior depending on which system triggered the layout. Now there is exactly one algorithm and one basis for the decision making. The other key difference is how the chain is formed. This is based heavily on the idea Andy mentioned of keeping a worklist of blocks that are viable layout successors based on the CFG. Having this set allows us to consistently select the best layout successor for each block. It is expensive though. The code here remains very rough. There is a lot that needs to be done to clean up the code, and to make the runtime cost of this pass much lower. Very much WIP, but this was a giant chunk of code and I'd rather folks see it sooner than later. Everything remains behind a flag of course. I've added a couple of tests to exercise the issues that this iteration was motivated by: loop structure preservation. I've also fixed one test that was exhibiting the broken behavior of the previous version. llvm-svn: 144495
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- Nov 02, 2011
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Chandler Carruth authored
the mailing list. Suggestions for other statistics to collect would be awesome. =] Currently these are implemented as a separate pass guarded by a separate flag. I'm not thrilled by that, but I wanted to be able to collect the statistics for the old code placement as well as the new in order to have a point of comparison. I'm planning on folding them into the single pass if / when there is only one pass of interest. llvm-svn: 143537
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- Oct 24, 2011
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Chandler Carruth authored
used it. Fixes an unused variable warning from GCC on release builds. llvm-svn: 142799
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- Oct 23, 2011
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Chandler Carruth authored
to get important constant branch probabilities and use them for finding the best branch out of a set of possibilities. llvm-svn: 142762
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Chandler Carruth authored
llvm-svn: 142761
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Chandler Carruth authored
discussions with Andy. Fundamentally, the previous algorithm is both counter productive on several fronts and prioritizing things which aren't necessarily the most important: static branch prediction. The new algorithm uses the existing loop CFG structure information to walk through the CFG itself to layout blocks. It coalesces adjacent blocks within the loop where the CFG allows based on the most likely path taken. Finally, it topologically orders the block chains that have been formed. This allows it to choose a (mostly) topologically valid ordering which still priorizes fallthrough within the structural constraints. As a final twist in the algorithm, it does violate the CFG when it discovers a "hot" edge, that is an edge that is more than 4x hotter than the competing edges in the CFG. These are forcibly merged into a fallthrough chain. Future transformations that need te be added are rotation of loop exit conditions to be fallthrough, and better isolation of cold block chains. I'm also planning on adding statistics to model how well the algorithm does at laying out blocks based on the probabilities it receives. The old tests mostly still pass, and I have some new tests to add, but the nested loops are still behaving very strangely. This almost seems like working-as-intended as it rotated the exit branch to be fallthrough, but I'm not convinced this is actually the best layout. It is well supported by the probabilities for loops we currently get, but those are pretty broken for nested loops, so this may change later. llvm-svn: 142743
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- Oct 21, 2011
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Chandler Carruth authored
it's a bit more plausible to use this instead of CodePlacementOpt. The code for this was shamelessly stolen from CodePlacementOpt, and then trimmed down a bit. There doesn't seem to be much utility in returning true/false from this pass as we may or may not have rewritten all of the blocks. Also, the statistic of counting how many loops were aligned doesn't seem terribly important so I removed it. If folks would like it to be included, I'm happy to add it back. This was probably the most egregious of the missing features, and now I'm going to start gathering some performance numbers and looking at specific loop structures that have different layout between the two. Test is updated to include both basic loop alignment and nested loop alignment. llvm-svn: 142645
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Chandler Carruth authored
block frequency analyses. This differs substantially from the existing block-placement pass in LLVM: 1) It operates on the Machine-IR in the CodeGen layer. This exposes much more (and more precise) information and opportunities. Also, the results are more stable due to fewer transforms ocurring after the pass runs. 2) It uses the generalized probability and frequency analyses. These can model static heuristics, code annotation derived heuristics as well as eventual profile loading. By basing the optimization on the analysis interface it can work from any (or a combination) of these inputs. 3) It uses a more aggressive algorithm, both building chains from tho bottom up to maximize benefit, and using an SCC-based walk to layout chains of blocks in a profitable ordering without O(N^2) iterations which the old pass involves. The pass is currently gated behind a flag, and not enabled by default because it still needs to grow some important features. Most notably, it needs to support loop aligning and careful layout of loop structures much as done by hand currently in CodePlacementOpt. Once it supports these, and has sufficient testing and quality tuning, it should replace both of these passes. Thanks to Nick Lewycky and Richard Smith for help authoring & debugging this, and to Jakob, Andy, Eric, Jim, and probably a few others I'm forgetting for reviewing and answering all my questions. Writing a backend pass is *sooo* much better now than it used to be. =D llvm-svn: 142641
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