Global load instruction aggregation based on dimensions of arrays

Most modern processors have some cache memories that are much faster than main memory. These cache memories function well if temporal or spatial localities in programs are enhanced; therefore, the continuous accesses to the same array that improves the localities can enhance effective utilization of the cache memories. In addition, because a multidimensional array can be regarded as an array of lower dimensional arrays, the continuous accesses to array references with the most similar indexes can enhance the utilization of them further. We propose a new code motion algorithm called MDGLIA that improves utilization of cache memory. MDGLIA moves each array reference immediately after the preceding references accessing the same array with the most similar indexes, and then delays it as late as possible without changing the access order. These two-step code motions contribute to not only improvement of the cache efficiency in the overall program but also suppression of register pressure. We implemented MDGLIA in a real compiler and evaluated it for matrix multiplication and SPEC benchmarks. The experimental results show that our algorithm reduces the number of cache misses in most cases.