关键词: 向量化, 循环分块, 分块因子选择, cache优化

Abstract:

The effect of tile sizes on vectorization tends to be ignored when performing loop tiling on a nested loop with a pathological problem size, which results in unaligned data access and performance degradation of tiled loop codes. This paper proposes a VECtorization-friendly Tile Size Selection（VEC-TSS） algorithm to solve the problem. The algorithm calculates the tile size of vectorizable loop by maximum vectorization profit, and it determines the tile sizes of other loops based on locality analysis and parallel granularity. Experimental results show that VEC-TSS algorithm achieves a better speedup over other two tile size selection algorithms on pathological-size loop cases. The results also prove that the VEC-TSS algorithm has good scalability.

Key words: vectorization, loop tiling, tile size selection, cache optimization