mlirSynth: Automatic, Retargetable Program Raising in Multi-Level IR
  using Program Synthesis
Alexander Brauckmann Elizabeth Polgreen Tobias Grosser Michael F. P. O'Boyle
MLIR is an emerging compiler infrastructure for modern hardware, but existing
programs cannot take advantage of MLIR's high-performance compilation if they
are described in lower-level general purpose languages. Consequently, to avoid
programs needing to be rewritten manually, this has led to efforts to
automatically raise lower-level to higher-level dialects in MLIR. However,
current methods rely on manually-defined raising rules, which limit their
applicability and make them challenging to maintain as MLIR dialects evolve.
  We present mlirSynth -- a novel approach which translates programs from
lower-level MLIR dialects to high-level ones without manually defined rules.
Instead, it uses available dialect definitions to construct a program space and
searches it effectively using type constraints and equivalences. We demonstrate
its effectiveness \revi{by raising C programs} to two distinct high-level MLIR
dialects, which enables us to use existing high-level dialect specific
compilation flows. On Polybench, we show a greater coverage than previous
approaches, resulting in geomean speedups of 2.5x (Intel) and 3.4x (AMD) over
state-of-the-art compilation flows for the C programming language. mlirSynth
also enables retargetability to domain-specific accelerators, resulting in a
geomean speedup of 21.6x on a TPU.