| A. Cohen. Parallelization via constrained storage mapping optimization. Lecture Notes in Computer Science, 1615:83--94, 1999. |
....there are AOV s shorter than anyUOV since the AOV must be valid for a smaller range of schedules. Finally, our frameworkgoesbeyond AOV s to unify the notion of occupancy vectors with known ane scheduling techniques. Another related approach to storage management for parallel programs is that of [3, 2, 11]. Given an ane schedule, 11] optimizes storage rst by restricting the size of each array dimension and then by combining distinct arrays via renaming. This work is extended in [3, 2] to consider storage mappings for a set of schedules, towards the end of capturing the tradeo between parallelism ....
....ane scheduling techniques. Another related approach to storage management for parallel programs is that of [3, 2, 11] Given an ane schedule, 11] optimizes storage rst by restricting the size of each array dimension and then by combining distinct arrays via renaming. This work is extended in [3, 2] to consider storage mappings for a set of schedules, towards the end of capturing the tradeo between parallelism and storage. However, these techniques utilize a storage mapping where, in an assignment, each array dimension is indexed by a loop counter and is modulated independently (e.g. ### ....
A. Cohen. Parallelization via constrained storage mapping optimization. Lecture Notes in Computer Science, 1615:83{??, 1999.
....such that some storage optimization can precede the nal choice of schedules. Integrating our approach with their framework could provide an interesting avenue for future research. Another related approach to storage management for parallel programs is that of Lefebvre, Feautrier, and Cohen [3, 2, 13]. Given an ane schedule, Lefebvre and Feautrier [13] optimize storage rst by restricting the size of each array dimension and then by combining distinct arrays via renaming. This work is extended by Cohen and Lefebvre [3, 2] to consider storage mappings for a set of schedules, towards the end of ....
....for parallel programs is that of Lefebvre, Feautrier, and Cohen [3, 2, 13] Given an ane schedule, Lefebvre and Feautrier [13] optimize storage rst by restricting the size of each array dimension and then by combining distinct arrays via renaming. This work is extended by Cohen and Lefebvre [3, 2] to consider storage mappings for a set of schedules, towards the end of capturing the tradeo between parallelism and storage. However, these techniques utilize a storage mapping where, in an assignment, each array dimension is indexed by a loop counter and is modulated independently (e.g. A[i ....
A. Cohen. Parallelization via constrained storage mapping optimization. Lecture Notes in Computer Science, 1615:83-94, 1999.
....are AOV s shorter than any UOV since the AOV must be valid for a smaller range of schedules. Finally, our framework goes beyond AOV s to unify the notion of occupancy vectors with known ane scheduling techniques. Another related approach to storage management for parallel programs is that of [3, 2, 11]. Given an ane schedule, 11] optimizes storage rst by restricting the size of each array dimension and then by combining distinct arrays via renaming. This work is extended in [3, 2] to consider storage mappings for a set of schedules, towards the end of capturing the tradeo between parallelism ....
....ane scheduling techniques. Another related approach to storage management for parallel programs is that of [3, 2, 11] Given an ane schedule, 11] optimizes storage rst by restricting the size of each array dimension and then by combining distinct arrays via renaming. This work is extended in [3, 2] to consider storage mappings for a set of schedules, towards the end of capturing the tradeo between parallelism and storage. However, these techniques utilize a storage mapping where, in an assignment, each array dimension is indexed by a loop counter and is modulated independently (e.g. A[i ....
A. Cohen. Parallelization via constrained storage mapping optimization. Lecture Notes in Computer Science, 1615:83{??, 1999.
....nested loop, our method applies to general ane dependences across statements and loop nests. Moreover, our framework goes beyond AOV s to unify the notion of occupancy vectors with known ane scheduling techniques. Another related approach to storage management for parallel programs is that of [3, 2, 11]. Given an ane schedule, 11] optimizes storage rst by restricting the size of each array dimension and then by combining distinct arrays via renaming. This work is extended in [3, 2] to consider storage mappings for a set of schedules, towards the end of capturing the tradeo between parallelism ....
....ane scheduling techniques. Another related approach to storage management for parallel programs is that of [3, 2, 11] Given an ane schedule, 11] optimizes storage rst by restricting the size of each array dimension and then by combining distinct arrays via renaming. This work is extended in [3, 2] to consider storage mappings for a set of schedules, towards the end of capturing the tradeo between parallelism and storage. However, these techniques utilize a storage mapping where, in an assignment, each array dimension is indexed by a loop counter and is modulated independently (e.g. A[i ....
A. Cohen. Parallelization via constrained storage mapping optimization. Lecture Notes in Computer Science, 1615:83-94, 1999.
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A. Cohen. Parallelization via constrained storage mapping optimization. Lecture Notes in Computer Science, 1615:83--94, 1999.
No context found.
A. Cohen. Parallelization via constrained storage mapping optimization. Lecture Notes in Computer Science, 1615:83--94, 1999.
No context found.
A. Cohen. Parallelization via constrained storage mapping optimization. Lecture Notes in Computer Science, 1615:83--94, 1999.
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