Tile size selection using cache organization and data layout

When dense matrix computations are too large to fit in cache, previous research proposes tiling to reduce or eliminate capacity misses. This paper presents a new algorithm for choosing problem-size dependent tile sizes based on the cache size and cache line size for a direct-mapped cache. The algorithm eliminates both capacity and self-interference misses and reduces cross-interference misses. We measured simulated miss rates and execution times for our algorithm and two others on a variety of problem sizes and cache organizations. At higher set associativity, our algorithm does not always achieve the best performance. However on direct-mapped caches, our algorithm improves simulated miss rates and measured execution times when compared with previous work.