Home Reading Searching Subscribe Sponsors Statistics Posting Contact Spam Lists Links About Hosting Filtering Features Download Marketing Archives FAQ Blog From: Adam Nemet apple.com> Subject: RFC: Loop distribution/Partial vectorization Newsgroups: gmane.comp.compilers.llvm.devel Date: Monday 12th January 2015 18:42:36 UTC (over 3 years ago) ```Hi, We'd like to propose new Loop Distribution pass. The main motivation is to allow partial vectorization of loops. One such example is the main loop of 456.hmmer in SpecINT_2006. The current version of the patch improves hmmer by 24% on ARM64 and 18% on X86. The goal of the pass is to distribute a loop that can't be vectorized because of memory dependence cycles. The pass splits the part with cycles into a new loop making the remainder of the loop a candidate for vectorization. E.g.: for (k = 0; k < M; k++) { S1: MC[k+1] = … // Cycle in S2 due to DC[k+1] -> DC[k] loop-carried dependence S2: DC[k+1] = DC[k], MC[k] } => (Loop Distribute) for (k = 0; k < M; k++) { S1: MC[k+1] = ... } for (k = 0; k < M; k++) { S2: DC[k+1] = DC[k], MC[k] } => (Loop Vectorize S1) for (k = 0; k < M; k += 4) { S1: MC[k+1:k+5] = ... } for (k = 0; k < M; k++) { S2: DC[k+1] = DC[k], MC[k] } I'd like to collect feedback on the design decisions made so far. These are implemented in a proof-of-concept patch (http://reviews.llvm.org/D6930 ). Here is the list of design choices: - Loop Distribution is implemented as a separate pass to be run before the Loop Vectorizer. - The pass reuses the Memory Dependence Checker framework from the Loop Vectorizer. This along with the AccessAnalysis class is split out into a new LoopAccessAnalysis class. We may want to turn this into an analysis pass on its own. - It also reuses the Run-time Memory Check code from the Loop Vectorizer. The hmmer loop requires memchecks. This is again captured by the same LoopAccessAnalysis class. - The actual loop distribution is implemented as follows: - The list of unsafe memory dependencies is computed for the loop. Unsafe means that the dependence may be part of a cycle (this is what the current framework provides). - Partitions are created for each set of unsafe dependences. - Partitions are created for each of the remaining stores not yet encountered. The order of the partitions preserve the original order of the dependent memory accesses. - Simple partition merging is performed to minimize the number of new loops. - Partitions are populated with the other dependent instructions by following the SSA use-def chains and control dependence edges. - Finally, the actual distribution is performed by creating a loop for each partition. For each partition we clone the loop and remove all the instructions that don't belong to the partition. - Also, if run-time memory checks are necessary, these are emitted. We keep an original version of the loop around to branch too if the checks fail. My plan is to proceed with the following steps: - Bring the current functionality to trunk by splitting off smaller patches from the current patch and completing them. The final commit will enable loop distribution with a command-line flag or a loop hint. - Explore and fine-tune the proper cost model for loop distribution to allow partial vectorization. This is essentially whether to partition and what these partitions should be. Currently instructions are mapped to partitions using a simple heuristics to create a vectorizable partitions. We may need to interact with the vectorizer to make sure the vectorization will actually happen and it will be overall profitable. - Explore other potentials for loop distribution, e.g.: - Partial vectorization of loops that can't be if-converted - Classic loop distribution to improve spatial locality - Compute the Program Dependence Graph rather than the list of unsafe memory accesses and allow reordering of memory operations - Distribute a loop in order to recognize parts as loop idioms Long term, loop distribution could also become a transformation utility (Transform/Util). That way, the loop transformation passes could use it to strip the loop from parts that inhibits the given optimization. Please let me know if you have feedback either on the design or on the next steps. Thanks, Adam```
CD: 12ms