Customized Monte Carlo Tree Search for LLVM/Polly’s Composable Loop Optimization Transformations. (arXiv:2105.04555v1 [cs.PL])

Polly is the LLVM project’s polyhedral loop nest optimizer. Recently,
user-directed loop transformation pragmas were proposed based on LLVM/Clang and
Polly. The search space exposed by the transformation pragmas is a tree,
wherein each node represents a specific combination of loop transformations
that can be applied to the code resulting from the parent node’s loop
transformations. We have developed a search algorithm based on Monte Carlo tree
search (MCTS) to find the best combination of loop transformations. Our
algorithm consists of two phases: exploring loop transformations at different
depths of the tree to identify promising regions in the tree search space and
exploiting those regions by performing a local search. Moreover, a restart
mechanism is used to avoid the MCTS getting trapped in a local solution. The
best and worst solutions are transferred from the previous phases of the
restarts to leverage the search history. We compare our approach with random,
greedy, and breadth-first search methods on PolyBench kernels and ECP proxy
applications. Experimental results show that our MCTS algorithm finds pragma
combinations with a speedup of 2.3x over Polly’s heuristic optimizations on



Related post