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An Approach for Code Generation in the Sparse Polyhedral Framework
  • Michelle Mills Strout, Colorado State University
  • Alan LaMielle, Colorado State University
  • Larry Carter, Colorado State University
  • Jeanne Ferrante, Colorado State University
  • Barbara Kreaseck, Colorado State University
  • Catherine Olschanowsky, Colorado State University
Applications that manipulate sparse data structures contain memory reference patterns that are unknown at compile time due to indirect accesses such as A[B[i]]. To exploit parallelism and improve locality in such applications, prior work has developed a number of run-time reordering transformations (RTRTs). This paper presents the Sparse Polyhedral Framework (SPF) for specifying RTRTs and compositions thereof and algorithms for automatically generating efficient inspector and executor code to implement such transformations. Experimental results indicate that the performance of automatically generated inspectors and executors competes with the performance of hand-written ones in some cases
Publication Date
December 24, 2013
Citation Information
Michelle Mills Strout, Alan LaMielle, Larry Carter, Jeanne Ferrante, et al.. "An Approach for Code Generation in the Sparse Polyhedral Framework" (2013)
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