Proceedings of the 15th ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages - POPL '88 1988
DOI: 10.1145/73560.73588
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Supernode partitioning

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Cited by 463 publications
(263 citation statements)
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“…This is why we restrict related work only to techniques aimed at automatic generation of tiled code. There has been a considerable amount of research into tiling, demonstrating how to aggregate a set of loop nest iterations into tiles with each tile as an atomic macro statement, from pioneer papers (Irigoin and Triolet, 1988;Wolf and Lam, 1991;Ramanujam and Sadayappan, 1992) to those presenting advanced techniques (Bondhugula et al, 2008a;Griebl, 2004;Lim et al, 1999;Wonnacott and Strout, 2013). Several popular frameworks are used to produce tiled code automatically: the classic polyhedral model (Feautrier, 1992a;1992b;Lim and Lam, 1994;Bondhugula et al, 2008a), the sparse polyhedral model (Strout et al, 2004), the non-polyhedral model (Kim and Rajopadhye, 2009), and iteration space slicing (Pugh and Rosser, 1997;.…”
Section: Related Workmentioning
confidence: 99%
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“…This is why we restrict related work only to techniques aimed at automatic generation of tiled code. There has been a considerable amount of research into tiling, demonstrating how to aggregate a set of loop nest iterations into tiles with each tile as an atomic macro statement, from pioneer papers (Irigoin and Triolet, 1988;Wolf and Lam, 1991;Ramanujam and Sadayappan, 1992) to those presenting advanced techniques (Bondhugula et al, 2008a;Griebl, 2004;Lim et al, 1999;Wonnacott and Strout, 2013). Several popular frameworks are used to produce tiled code automatically: the classic polyhedral model (Feautrier, 1992a;1992b;Lim and Lam, 1994;Bondhugula et al, 2008a), the sparse polyhedral model (Strout et al, 2004), the non-polyhedral model (Kim and Rajopadhye, 2009), and iteration space slicing (Pugh and Rosser, 1997;.…”
Section: Related Workmentioning
confidence: 99%
“…Tiling (Irigoin and Triolet, 1988;Wolf and Lam, 1991;Ramanujam and Sadayappan, 1992;Xue, 1996;Bondhugula et al, 2008a;Griebl, 2004;Lim et al, 1999) is a very important iteration reordering transformation for both improving data locality and coarsening the granularity of parallelism.…”
Section: Introductionmentioning
confidence: 99%
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“…Irigoin and Triolet's supernode partitioning approach [21] divides an iteration space of a loop nest into nodes with several goals : vector computation within a node, loop tiling for data reuse and parallelism between tiles. In [4], Sakellariou discusses the necessary condition for partitioning a loop nest across different processors with equal workload.…”
Section: Previous Workmentioning
confidence: 99%
“…This space can then be tiled, breaking up the computations in an attempt to group those that use the same data together thereby increase data locality. Tiling as a performance optimization has been studied extensively and has been shown to make code more efficient [15,6,12,16].…”
Section: Introductionmentioning
confidence: 99%