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Co-optimizing Dataflow Graphs and Actors with MLIR
- Source :
- 2022 IEEE Workshop on Signal Processing Systems (SiPS), 2022 IEEE Workshop on Signal Processing Systems (SiPS), Nov 2022, Rennes, France
- Publication Year :
- 2022
- Publisher :
- HAL CCSD, 2022.
-
Abstract
- International audience; Dataflow programming is considered a good solution for the implementation of parallel signal processing applications. However, the strict separation between kernel and coordination codes limits the variety of possible optimizations and the compatibility with state-of-the-art compiler frameworks. We present a prototype static dataflow compiler, built with the LLVM MLIR framework, that overcomes these limitations and enables a previously impossible combination of optimization strategies that leverages information from the dataflow topology. Initial results show 30% wall time improvement and 53% memory usage improvement on a video processing workload.
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- 2022 IEEE Workshop on Signal Processing Systems (SiPS), 2022 IEEE Workshop on Signal Processing Systems (SiPS), Nov 2022, Rennes, France
- Accession number :
- edsair.doi.dedup.....206920b0e9cade7dcc780fadd81ea49a