We introduce REPTILE, a compiler that performs tiling optimizations for programs expressed as mathematical recurrence equations. REPTILE recursively decomposes a recurrence program into a set of unique tiles and then simplifies each into a different set of recurrences. Given declarative user specifications of recurrence equations, optimizations, and optional mappings of recurrence subexpressions to external libraries calls, REPTILE generates C code that composes compiler-generated loops with calls to external hand-optimized libraries. We show that for direct linear solvers expressible as recurrence equations, the generated C code matches and often exceeds the performance of standard hand-optimized libraries. We evaluate REPTILE’s generated C code against hand-optimized implementations of linear solvers in Intel MKL, as well as two nonsolver recurrences from bioinformatics: Needleman-Wunsch and Smith-Waterman. When the user provides good tiling specifications, REPTILE achieves parity with MKL, achieving between 0.79−1.27x speedup for the LU decomposition, 0.97−1.21x speedup for the Cholesky decomposition, 1.61x−2.72x for lower triangular matrix inversion, 1.01−1.14x speedup for triangular solve with multiple right-hand sides, and 1.14−1.73x speedup over handwritten implementations of the bioinformatics recurrences.

@article{paperbot2953,
  title = {REPTILE: Performant Tiling of Recurrences},
  author = {Muhammad Usman Tariq and Shiv Sundram and Fredrik Kjolstad},
  journal = {Proceedings of the ACM on Programming Languages},
  volume = {9},
  number = {OOPSLA2},
  year = {2025},
  doi = {10.1145/3763074}
}