on Linear Cache Optimization & Vectorization 15 - 411 : Compiler Design André Platzer
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چکیده
We have seen a number of loop transformations, but they all have been different, needing different analysis and implementation. However, a closer look reveals that the previous list of loop transformations (permutation, reversal, skewing) all follow a general pattern of linear loop transformations. Each of those transformations (and combinations and many others) can be represented by unimodular linear transformations. That is, such a transformation on n loops corresponds to an n × n integer matrix U ∈ Zn×n with determinant detU = ±1. Because of the unit determinant detU , they actually form a group, because we can form inverses
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Notes on Linear Cache Optimization & Vectorization 15 - 411 : Compiler Design André Platzer
The big missing questions on cache optimization are how and when generally to transform loops? What is the best choice to find a loop transformation? Is there a big common systematic picture? How to get fast by vectorizing and/or parallelizing loops after the loop transformations have made some loops parallelizable? And, finally, how can we use more fancy transformations for complicated problems.
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تاریخ انتشار 2010