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@bourgesl bourgesl commented Apr 20, 2023

  • improved mixed insertion sort (makes whole sorting faster)
  • introduced Radix which sort shows several times boost of performance and has linear complexity instead of n*ln(n)
  • improved merging sort for almost sorted data
  • optimized parallel sorting
  • improved step for pivot candidates and pivot partitioning
  • extended existing tests
  • added benchmarking JMH tests
  • suggested better buffer allocation: if no memory, it is switched to in-place sorting with no OutOfMemoryError, threshold is 1/16th heap

I am going on previous PR by Vladimir Yaroslavskyi: #3938


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 ⚠️ Found copyright format issue for oracle in [test/jdk/javax/swing/JFileChooser/6738668/bug6738668.java]

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Issue

  • JDK-8266431: Dual-Pivot Quicksort improvements (Radix sort) (Enhancement - P4)

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👋 Welcome back lbourges! A progress list of the required criteria for merging this PR into master will be added to the body of your pull request. There are additional pull request commands available for use with this pull request.

@openjdk openjdk bot added the rfr Pull request is ready for review label Apr 20, 2023
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@openjdk openjdk bot added rfr Pull request is ready for review and removed rfr Pull request is ready for review labels Apr 23, 2023
@iaroslavski
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The changes look fine for me, approve this PR.

@bourgesl
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@AlanBateman @rose00 @mbreinhold Could any core-libs reviewer have a look ?
No hurry as jdk21 rdp0 is coming but later in june ?

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⚠️ @bourgesl This pull request contains merges that bring in commits not present in the target repository. Since this is not a "merge style" pull request, these changes will be squashed when this pull request in integrated. If this is your intention, then please ignore this message. If you want to preserve the commit structure, you must change the title of this pull request to Merge <project>:<branch> where <project> is the name of another project in the OpenJDK organization (for example Merge jdk:master).

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@bourgesl This pull request has been inactive for more than 4 weeks and will be automatically closed if another 4 weeks passes without any activity. To avoid this, simply add a new comment to the pull request. Feel free to ask for assistance if you need help with progressing this pull request towards integration!

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Please @AlanBateman could you review this PR?

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Hello, please see an implementation of x86 SIMD sort for Java here: #14227

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These benchmarks are all small arrays. We need to check for possible regressions here.
Also, I'm rather concerned that we might lose the data from this PR.

@bourgesl
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Keeping this PR alive

@bourgesl
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These benchmarks are all small arrays. We need to check for possible regressions here.
The JMH ArraysSort tests arrays of length 800 to 2 million elements.
Is it not enough for smaller or larger arrays ?

Also, I'm rather concerned that we might lose the data from this PR.
Keep alive done!

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These benchmarks are all small arrays. We need to check for possible regressions here.

Sorry, all large arrays. I suspect that the average-length sort is not represented.

Also, I'm rather concerned that we might lose the data from this PR.

How does keep alive work? Will the data from that external web site still be here for the reader in 15 years' time?

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pavelrappo commented Aug 17, 2023

How does keep alive work? Will the data from that external web site still be here for the reader in 15 years' time?

Hm... I thought that at least full webrevs are stored somewhere on https://cr.openjdk.org/. Turns out they aren't. They are stored on https://openjdk.github.io/cr/.

Okay, a cheap thing to do now is to ask the Web Archive to store it, which I just did:

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Hi team,
@AlanBateman, @rose00, @mbreinhold

There are a big efforts now to improve sorting with x86_64 AVX512
#14227, no changes of
Dual-Pivot Quicksort logic.

But at the same time this PR offers algorithmic improvements,
like optimized insertion sort, merging sort, better partitioning
and Radix sort for fully random data. Radix sort has linear complexity
instead of n*ln(n), much faster!. Also we handle properly situation if
no enough memory for additional buffer, now we will face with OOM.

Alan, you mentioned that DualPivotQuicksort will need detailed review.
Can we go ahead and start reviewing? Laurent checked performance,
JMH results look fine.

I think it would be logical to integrate new DualPivotQuicksort first,
and then apply AVX512 changes.

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Alan, you mentioned that DualPivotQuicksort will need detailed review. Can we go ahead and start reviewing? Laurent checked performance, JMH results look fine.

As before, I think the main question with this change is whether adding radix sort to the mix is worth the complexity and additional code to maintain. Also as we discussed in the previous PR, the additional memory needed for the radix sort may have an effect on other things that are going on concurrently. I know it has been updated to handle OOME but I think potential reviewers would need to be comfortable with that part.

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Hi Alan (@AlanBateman) and team,

I understand your doubts about Radix sort, let's me to provide my thoughts.

Code of Radix sort is about 10% of all code and very clear for understanding: scan digits + then place elements according histogram. Other sorting algorithms have more complexity (like merging sort, quicksort partitioning, heap sort). Therefore, I don't expect problems with maintaining.

Why Radix sort is important? Even Quicksort is very fast, but it relies on comparability of elements only and knows nothing about nature of elements to be sorted. Radix sort knows the structure of elements (32 or 64 bits) and therefore works faster (on random data). I was asked many times why we don't use Radix sort, so the idea is not new. Introducing of Radix sort is like using of counting sort for byte/short/char, the same approach.

Existing version of sort() will request additional memory, if tryMergingSort() detects already sorted subsequences. In this case Radix sort or Quicksort will not be invoked at all. Radix sort is invoked, if merging sort is not completed (and therefore, no allocated memory). Additional memory is requested by either merging sort or Radix sort, not by both algorithms on the same input. It means these algorithms never request double memory. Memory effect (merging sort and Radix sort) is not summarized. In case of parallel sorting the additional buffer allocated for parallel merge sort will be reused by tryMergingSort() as well as by Radix sort.

Summary: the size of total requested memory always equals to the size of part to be sorted (not more), no any duplicates.

Need to say that Radix sort is invoked not on all inputs, many inputs are covered by Quicksort or merging sort. If Quicksort suggests O(n*ln(n)), Radix sort shows linear, much better, O(n) time! As it was mentioned before, we added check against OOM, sorting will be completed successfully in any case. Existing implementation will fail with error, if there is no enough memory.

In few words, Radix sort is simple and it impacts not more than already introduced algorithms in JDK.

I encourage reviewers to look at this PR.

Thank you,
Vladimir

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Hi team,

@AlanBateman Alan,
Are there other questions/comments regarding to Radix sort?

Reviewers,
@rose00 John Rose
@mbreinhold Mark Reinhold
@pavelrappo Pavel Rappo
@theRealAph Andrew Haley
@schlosna David Schlosnagle
@PaulSandoz Paul Sandoz
@vnkozlov Vladimir Kozlov
@erikj79 Erik Joelsson
@jatin-bhateja Jatin Bhateja
@sviswa7 Sandhya Viswanathan
@vamsi-parasa Srinivas Vamsi Parasa

We have two improvements of sorting: algorithmic approach (this PR) and based on AVX512 (#14227).
Both changes are important, could you please find time to look at this PR?

Thank you,
Vladimir

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pavelrappo commented Sep 15, 2023

@pavelrappo Pavel Rappo

Vladimir, please do not consider me a reviewer. I'm merely a passer-by: I didn't review a single line of this PR, nor do I have expertise to do so.

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Alan, you mentioned that DualPivotQuicksort will need detailed review. Can we go ahead and start reviewing? Laurent checked performance, JMH results look fine.

As before, I think the main question with this change is whether adding radix sort to the mix is worth the complexity and additional code to maintain. Also as we discussed in the previous PR, the additional memory needed for the radix sort may have an effect on other things that are going on concurrently. I know it has been updated to handle OOME but I think potential reviewers would need to be comfortable with that part.

I too share concerns about the potential increased use of memory for sorting ints/longs/floats/doubles. With modern SIMD hardware and data parallel techniques we can apply quicksort much more efficiently. I think it is important to determine to what extent this reduces the need for radix sort. To determine that we would need to carefully measure against the AVX-512 implementation (with ongoing improvements) with appropriately initialized data to sort, and further measure against an AVX2 version.

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Alan, you mentioned that DualPivotQuicksort will need detailed review. Can we go ahead and start reviewing? Laurent checked performance, JMH results look fine.

As before, I think the main question with this change is whether adding radix sort to the mix is worth the complexity and additional code to maintain. Also as we discussed in the previous PR, the additional memory needed for the radix sort may have an effect on other things that are going on concurrently. I know it has been updated to handle OOME but I think potential reviewers would need to be comfortable with that part.

I too share concerns about the potential increased use of memory for sorting ints/longs/floats/doubles. With modern SIMD hardware and data parallel techniques we can apply quicksort much more efficiently. I think it is important to determine to what extent this reduces the need for radix sort. To determine that we would need to carefully measure against the AVX-512 implementation (with ongoing improvements) with appropriately initialized data to sort, and further measure against an AVX2 version.

Hi @PaulSandoz Paul, @AlanBateman Alan,

I agree that additional memory must not change current behavior of the core.

When parallel sort was introduced in JDK 8, parallel implementation with additional
memory in merge sort went to the new method Arrays.parallelSort instead of Arrays.sort
to be sure that existing applications will not broken.

We take care of memory usages in sequential sorting, therefore I suggest the
following variant: what if we introduce Radix sort for parallel sorting only?

There are no memory changes in sequential sorting and in parallel sorting Radix
sort will reuse buffer from parallel merge sort. It means there is no potential
increased use of memory at all, no risk, we will keep current behavior. It is easy
to adapt new implementation: one changed line for each type int/long/float/double.

Paul, Alan,
Do you agree with such idea?

@iaroslavski
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Hi Paul (@PaulSandoz), Alan (@AlanBateman),
Any update? Do you agree with Radix sort in parallel case only?

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delay due to holidays and vacations

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@bourgesl This pull request has been inactive for more than 4 weeks and will be automatically closed if another 4 weeks passes without any activity. To avoid this, simply add a new comment to the pull request. Feel free to ask for assistance if you need help with progressing this pull request towards integration!

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Keep alive

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Keep alive

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Sorting of short/byte/char is in progress

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Good luck vladimir...
hope to have free cycles soon...

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Keep alive for few cycles more

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Sorting of short/byte/char is still in progress

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Sorting of short/byte/char is almost finished

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Sorting of short/byte/char is almost finished

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minborg commented Mar 10, 2025

Hi. I've seen this PR being worked on for a long time. Did you discuss the motivation and objectives for this PR in the relevant mailing list as indicated in the JDK issue? Reviewing this PR seems like a handful and given new features like Valhalla and the Vector API will soon be available, did you consider waiting for those new features rather than pressing forward with this PR?

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Hi @minborg,

Thank you for your comments!

You're right, this is a long period of activity, please see the short history of it.

Dual-Pivot Quicksort was suggested and integrated into JDK 7 by Josh Bloch, John Bentley and me in September-November 2009. Later I improved the sorting several times faster in JDK 7, 8 and 14.

In April 2021 Laurent Bourges suggested adding Radix sort which is several times faster than Quicksort on a large array of random data. In May 2021 I created my PR, but my account was not enabled very fast, so I continued optimization. Later we had to move to Laurent's PR with new portions of optimizations.

As we discussed with Alan Bateman and Paul Sandoz, Radix sort will be applied to parallel sort only. Even though Radix sort is not called for sequential sorting, Dual-Pivot Quicksort became faster for many data types, like double/float, char/byte/short, on various inputs (both, sequential and parallel cases).

In August 2023 Vamsi Parsa improved the sorting using AVX512 instructions. It made sorting faster on Linux on Intel processors with AVX512. I can say my current changes speedup this AVX512-ed version, it happens due to different types of optimizations (algorithmic vs. instruction). My algorithmic changes don't correlate with new features (Valhalla / Vector API / etc.) and can be developed / integrated independently.

Now I have the final version of Dual-Pivot Quicksort with fine benchmarking results. I need time to check test coverage. I plan to create new PR under my account and publish updated classes and benchmarks within one month. I hope it makes sense.

@minborg, what do you think, what is your vision?

Best regards,
Vladimir

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minborg commented Mar 11, 2025

Thanks for the update @iaroslavski . I am a bit worried that it will be difficult to find reviewers for this PR since it has a relatively large spanning scope. But I might be wrong about that.

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Need time to check test coverage

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Need more time to check test coverage

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keep alive, need time to complete

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keep alive, need time to finish

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