DxTer: An Extensible Tool for Optimal Dataflow Program Generation

نویسندگان

  • Bryan Marker
  • Martin Schatz
  • Devin Matthews
  • Isil Dillig
  • Robert van de Geijn
  • Don Batory
چکیده

DxTer (pronounced “dexter”) is a tool for generating high-performance program implementations of an input dataflow graph. Given a specification S of a program in some domain D, DxTer uses its knowledge base for D to explore a space of implementations of S and outputs an optimal implementation with respect to the cost model in D. While DxTer search spaces can be massive (e.g., 10), this paper describes new techniques that allow DxTer to search such spaces and generate optimal code in seconds. In a case study, we apply DxTer to the domain of tensor contractions and show that DxTer generates programs that are competitive with (and sometimes superior to) a state-of-the-art tensor contraction tool.

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تاریخ انتشار 2015