Efficient Index Generation for Compiling Two-Level Mappings in Data-Parallel Programs

This paper presents compilation techniques used to compress holes, which are caused by the nonunit alignment stride in a two-level data-processor mapping. Holes are the memory locations mapped by useless template cells. To fully utilize the memory space, memory holes should be removed. In a two-level data-processor mapping, there is a repetitive pattern for array elements mapped onto processors. We classify blocks into classes and use a class table to record the distribution of each class in the first repetitive data distribution pattern. Similarly, data distribution on a processor also has a repetitive pattern. We use a compression table to record the distribution of each block in the first repetitive data distribution pattern on a processor. By using a class table and a compression table, hole compression can be easily and efficiently achieved. Compressing holes can save memory usage, improve spatial locality and further improve system performance. The proposed method is efficient, stable, and easy to implement. The experimental results do confirm the advantages of our proposed method over existing methods.