Improving memory performance of sorting algorithms

Abstract
Memory hierarchy considerations during sorting algorithm design and implementation play an important role in significantly improving execution performance. Existing algorithms mainly attempt to reduce capacity misses on direct-mapped caches. To reduce other types of cache misses that occur in the more common set-associative caches and the TLB, we restructure the mergesort and quicksort algorithms further by integrating tiling, padding, and buffering techniques and by repartitioning the data set. Our study shows that substantial performance improvements can be obtained using our new methods.

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