Cache Analysis of Non-uniform Distribution Sorting Algorithms
Naila Rahman, Rajeev Raman
Abstract
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Naila Rahman, Rajeev Raman
Abstract
Open-access reader
We analyse the average-case cache performance of distribution sorting algorithms in the case when keys are independently but not necessarily uniformly distributed. The analysis is for both `in-place' and `out-of-place' distribution sorting algorithms and is more accurate than the analysis presented in \cite{RRESA00}. In particular, this new analysis yields tighter upper and lower bounds when the keys are drawn from a uniform distribution. We use this analysis to tune the performance of the integer sorting algorithm MSB radix sort when it is used to sort independent uniform floating-point numbers (floats). Our tuned MSB radix sort algorithm comfortably outperforms a cache-tuned implementations of bucketsort \cite{RR99} and Quicksort when sorting uniform floats from $[0, 1)$.
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We analyse the average-case cache performance of distribution sorting algorithms in the case when keys are independently but not necessarily uniformly distributed. The analysis is for both `in-place' and `out-of-place' distribution sorting algorithms and is more accurate than the analysis presented in \cite{RRESA00}. In particular, this new analysis yields tighter upper and lower bounds when the keys are drawn from a uniform distribution. We use this analysis to tune the performance of the integer sorting algorithm MSB radix sort when it is used to sort independent uniform floating-point numbers (floats). Our tuned MSB radix sort algorithm comfortably outperforms a cache-tuned implementations of bucketsort \cite{RR99} and Quicksort when sorting uniform floats from $[0, 1)$.
Key concepts: Computer science, Sorting, Cache, Parallel computing, Sorting algorithm, Algorithm