Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  studies the relationship beten storage requirements and performance. Storage-related dependences inhibit optimizations for locality and parallelism. Techniques such as renaming and array expansion can eliminate all storage-related dependences, but do so at the expense of increased storage.  introduces the  universal occupancy vector  (UOV) for loops with a regular stencil of dependences. The UOV provides a schedule-independent storage reuse pattern that introduces no further dependences (other than those implied by true flow dependences). OV-mapped code requires less storage than full array expansion and only slightly more storage than schedule-dependent minimal storage. show that determine if a vector is a UOV is NPcomplete. Hover, an easily constructed but possibly nonminimal UOV can be used.  also present a branch and bound algorithm which finds the minimal UOV, while still maintaining a legal UOV at all times.Our experimental results show that the use of OV-mapped storage, coupled with tiling for locality, achieves better performance than tiling after array expansion, and accommodates larger problem sizes than untilable, storage-optimized code. F'urthermore, storage mapping based on the UOV introduces negligible runtime overhead.
['Michelle Mills Strout', 'Larry Carter', 'Jeanne Ferrante', 'Beth Simon']
I am writing a research paper on a idea Schedule-independent storage mapping for loops
[{"from": "human", "value": "I am writing a research paper on a idea Schedule-independent storage mapping for loops"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  studies the relationship beten storage requirements and performance. Storage-related dependences inhibit optimizations for locality and parallelism. Techniques such as renaming and array expansion can eliminate all storage-related dependences, but do so at the expense of increased storage.  introduces the  universal occupancy vector  (UOV) for loops with a regular stencil of dependences. The UOV provides a schedule-independent storage reuse pattern that introduces no further dependences (other than those implied by true flow dependences). OV-mapped code requires less storage than full array expansion and only slightly more storage than schedule-dependent minimal storage. show that determine if a vector is a UOV is NPcomplete. Hover, an easily constructed but possibly nonminimal UOV can be used.  also present a branch and bound algorithm which finds the minimal UOV, while still maintaining a legal UOV at all times.Our experimental results show that the use of OV-mapped storage, coupled with tiling for locality, achieves better performance than tiling after array expansion, and accommodates larger problem sizes than untilable, storage-optimized code. F'urthermore, storage mapping based on the UOV introduces negligible runtime overhead."}]