In-place Parallel Super Scalar Samplesort (IPS$^4$o) · HackerPapers discussions

In-place Parallel Super Scalar Samplesort (IPS$^4$o) — mentioned by ipsofacto

Sun, 17 May 2020 18:09:58 GMT

There's an even better branch-free (super scalar) sorting algorithm: "In-place Parallel Super Scalar Samplesort (IPS4o)" which we started using: https://github.com/SaschaWitt/ips4o https://arxiv.org/abs/1705.02257 As an example, to sort 10 million random longs on my computer it takes std::sort 766 ms (roughly in line with Andrei's numbers) and ips4o::sort takes 274 ms. [edit:formatting]

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In-place Parallel Super Scalar Samplesort (IPS$^4$o) — mentioned by lorenzhs

Fri, 31 Aug 2018 11:28:11 GMT

Especially when targeting realistic machine models, there are a lot of things that are suboptimal about the classical sorting algorithms like quicksort or mergesort. For example, a quicksort with perfect choice of pivot will incur a branch miss with probability 50% for every element. That's not something classical complexity analysis measures, but on actual CPUs, branch misses have quite an impact (something like 10–15 cycles). Shameless plug for something I once built for a lecture to demonstrate this: https://github.com/lorenzhs/quicksort-pivot-imbalance For sorting algorithms that take the…

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In-place Parallel Super Scalar Samplesort (IPS$^4$o) — mentioned by lorenzhs

Fri, 30 Jun 2017 08:08:06 GMT

Don't count out sample-sort just yet, it lends itself to parallelisation very well and is blazingly fast. See https://arxiv.org/abs/1705.02257 (to be presented at ESA in September) for an in-place parallel implementation that overcomes the most important downsides of previous sample-sort implementations (linear additional space).

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In-place Parallel Super Scalar Samplesort (IPS$^4$o) — mentioned by lorenzhs

Fri, 30 Jun 2017 07:59:15 GMT

To illustrate the point about branch misprediction, I implemented quicksort with intentionally skewed pivot selection. You can see the results here: https://github.com/lorenzhs/quicksort-pivot-imbalance For this demo I'm sorting a permutation of the range 1 to n, so obtaining perfect or arbitrarily skewed pivots is free, which isn't realistic, but that's not the point. My experiments show that quicksort is fastest on my machine when 15% of the elements are on one side and 85% on the other. This is a tradeoff between branch prediction (if it always guesses "right side", it's right 85% of the…

Paper and discussion history. A mention is not an endorsement.