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Publications of SPCL

T. Ben-Nun, B. Ates, A. Calotoiu, T. Hoefler:
	Bridging Control-Centric and Data-Centric Optimization (In 2023 IEEE/ACM International Symposium on Code Generation and Optimization (CGO), pages 173-185, Feb. 2023) Publisher Reference Abstract With the rise of specialized hardware and new programming languages, code optimization has shifted its focus towards promoting data locality. Most production-grade compilers adopt a control-centric mindset - instruction-driven optimization augmented with scalar-based dataflow - whereas other approaches provide domain-specific and general purpose data movement minimization, which can miss important control-flow optimizations. As the two representations are not commutable, users must choose one over the other. In this paper, we explore how both control- and data-centric approaches can work in tandem via the Multi-Level Intermediate Representation (MLIR) framework. Through a combination of an MLIR dialect and specialized passes, we recover parametric, symbolic dataflow that can be optimized within the DaCe framework. We combine the two views into a single pipeline, called DCIR, showing that it is strictly more powerful than either view. On several benchmarks and a real-world application in C, we show that our proposed pipeline consistently outperforms MLIR and automatically uncovers new optimization opportunities with no additional effort. Documents download article:
	BibTeX
@inproceedings{,   author={Tal Ben-Nun and Berke Ates and Alexandru Calotoiu and Torsten Hoefler},   title={{Bridging Control-Centric and Data-Centric Optimization}},   year={2023},   month={02},   pages={173-185},   booktitle={2023 IEEE/ACM International Symposium on Code Generation and Optimization (CGO)},   doi={10.1145/3579990.3580018}, }