An MLIR Lowering Pipeline for Stencils at Wafer-Scale
Nicolai Stawinoga, David Katz, Anton Lydike, Justs Zarins, Nick Brown, George Bisbas, Tobias Grosser
摘要
The Cerebras Wafer-Scale Engine (WSE) delivers performance at an unprecedented scale of over 900,000 compute units, all connected via a single-wafer on-chip interconnect. Initially designed for AI, the WSE architecture is also well-suited for High Performance Computing (HPC). However, its distributed asynchronous programming model diverges significantly from the simple sequential or bulk-synchronous programs that one would typically derive for a given mathematical program description. Targeting the WSE requires a bespoke re-implementation when porting existing code. The absence of WSE support in compilers such as MLIR, meant that there was little hope for automating this process.
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- Fast stencil-code computation on a wafer-scale processorKamil Rocki, Dirk Van Essendelft, Ilya Sharapov, Robert Schreiber 等SC 2020 · 被引用 69 次
- Scalable Distributed High-Order Stencil ComputationsMathias Jacquelin, Mauricio Araya-Polo, Jie MengSC 2022 · 被引用 17 次
- IRDL: an IR definition language for SSA compilersMathieu Fehr, Jeff Niu, River Riddle, Mehdi Amini 等PLDI 2022 · 被引用 13 次
- A shared compilation stack for distributed-memory parallelism in stencil DSLsGeorge Bisbas, Anton Lydike, Emilien Bauer, Nick Brown 等ASPLOS 2024 · 被引用 11 次
- Automated Code Generation of High-Order Stencils for a Dataflow ArchitectureRyuichi Sai, John M. Mellor-Crummey, Jinfan Xu, Mauricio Araya-PoloSC 2024 · 被引用 8 次
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