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MLIR has become popular since it was open sourced in 2019. A sub-project ofLLVM, the flexibility provided by MLIR to represent IntermediateRepresentations (IR) as dialects at different abstraction levels, to mix these,and to leverage transformations between dialects provides opportunities forautomated program optimisation and parallelisation. In addition to generalpurpose compilers built upon MLIR, domain specific abstractions have also beendeveloped.  In this paper we explore complimenting the Flang MLIR general purposecompiler by combining with the domain specific Open Earth Compiler's MLIRstencil dialect. Developing transformations to discover and extracts stencilsfrom Fortran, this specialisation delivers between a 2 and 10 times performanceimprovement for our benchmarks on a Cray supercomputer compared to using Flangalone. Furthermore, by leveraging existing MLIR transformations we develop anauto-parallelisation approach targeting multi-threaded and distributed memoryparallelism, and optimised execution on GPUs, without any modifications to theserial Fortran source code.

Fortran performance optimisation and auto-parallelisation by leveraging MLIR-based domain specific abstractions in Flang