Presentation
OpenSHMEM MLIR: A Dialect for Compile-Time Optimization of One-Sided Communications
DescriptionCommunication increasingly limits performance in high-performance computing (HPC), yet mainstream compilers focus on computation because communication intent is lost early in compilation. OpenSHMEM offers a one-sided Partitioned Global Address Space (PGAS) model with symmetric memory and explicit synchronization, but lowering to opaque runtime calls hides these semantics from analysis.
We present an OpenSHMEM dialect for Multi-Level Intermediate Representation (MLIR) that preserves one-sided communication, symmetric memory, and team/context structure as first-class intermediate representation (IR) constructs. Retaining these semantics prior to lowering enables precise, correctness-preserving optimizations that are difficult to recover from LLVM IR. The dialect integrates with existing MLIR/LLVM passes while directly representing communication and synchronization intent.
We demonstrate four transformations: recording the number of processing elements, fusing compatible atomics, converting blocking operations to non-blocking forms when safe, and aggregating small messages. These examples show how explicit OpenSHMEM semantics enable communication-aware optimization and lay the groundwork for richer cross-layer analyses.
We present an OpenSHMEM dialect for Multi-Level Intermediate Representation (MLIR) that preserves one-sided communication, symmetric memory, and team/context structure as first-class intermediate representation (IR) constructs. Retaining these semantics prior to lowering enables precise, correctness-preserving optimizations that are difficult to recover from LLVM IR. The dialect integrates with existing MLIR/LLVM passes while directly representing communication and synchronization intent.
We demonstrate four transformations: recording the number of processing elements, fusing compatible atomics, converting blocking operations to non-blocking forms when safe, and aggregating small messages. These examples show how explicit OpenSHMEM semantics enable communication-aware optimization and lay the groundwork for richer cross-layer analyses.
Author/Presenters
Event Type
Workshop
TimeMonday, 17 November 20253:30pm - 4:00pm CST
Location260