Journal
ACM TRANSACTIONS ON ARCHITECTURE AND CODE OPTIMIZATION
Volume 18, Issue 4, Pages -Publisher
ASSOC COMPUTING MACHINERY
DOI: 10.1145/3469030
Keywords
Weather and climate; stencil computations; intermediate representations
Funding
- European Research Council (ERC) under the European Union's Horizon 2020 programme (grant agreement DAPP) [678880]
- Swiss National Science Foundation under the Ambizione programme [PZ00P2168016]
- ARM Holdings plc
- Xilinx Inc
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The study shows that multilevel rewriting is efficient in compiler optimization, especially for the weather and climate domain. By designing domain-specific dialects and optimizations, the compiler was optimized and achieved better results than existing solutions.
Most compilers have a single core intermediate representation (IR) (e.g., LLVM) sometimes complemented with vaguely defined IR-like data structures. This IR is commonly low-level and close to machine instructions. As a result, optimizations relying on domain-specific information are either not possible or require complex analysis to recover the missing information. In contrast, multi-level rewriting instantiates a hierarchy of dialects (IRs), lowers programs level-by-level, and performs code transformations at the most suitable level. We demonstrate the effectiveness of this approach for the weather and climate domain. In particular, we develop a prototype compiler and design stencil- and GPU-specific dialects based on a set of newly introduced design principles. We find that two domain-specific optimizations (500 lines of code) realized on top of LLVM's extensible MLIR compiler infrastructure suffice to outperform state-of-the-art solutions. In essence, multilevel rewriting promises to herald the age of specialized compilers composed from domain- and target-specific dialects implemented on top of a shared infrastructure.
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