Deriving parametric multi-way recursive divide-and-conquer dynamic programming algorithms using polyhedral compilers

Abstract

We present a novel framework to automatically derive highly efficient parametric multi-way recursive divide-&-conquer algorithms for a class of dynamic programming (DP) problems. Standard two-way or any fixed R-way recursive divide- &-conquer algorithms may not fully exploit many-core processors. To run efficiently on a given machine, the value of R may need to be different for every level of recursion based on the number of processors available and the sizes of memory/- caches at different levels of the memory hierarchy. The set of R values that work well on a given machine may not work efficiently on another machine with a different set of machine parameters. To improve portability and efficiency, Multi-way Autogen generates parametric multi-way recursive divide-&- conquer algorithms where the value of R can be changed on the fly for every level of recursion. We present experimental results demonstrating the performance and scalability of the parallel programs produced by our framework.