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From: "Jon Harrop" <jon@ffconsultancy.com>
To: "Caml List" <caml-list@inria.fr>
Subject: [Caml-list] Parallel n-queens solver
Date: Mon, 25 Apr 2011 00:32:31 +0100	[thread overview]
Message-ID: <013e01cc02d7$e23b8f00$a6b2ad00$@ffconsultancy.com> (raw)

Gerd recently posted this article about parallelizing an n-queens solver in
OCaml:

  http://blog.camlcity.org/blog/multicore3.html

The idea is to reuse the same basic definitions and parallelize the program
simply by changing the "run" function. I have tried to translate this OCaml
to F# without benefit of being able to run the original OCaml code but I
have checked the results against the known solutions to this problem.

Here is Gerd's sequential OCaml:

module Sequential = struct
  let run n =
    let t0 = Unix.gettimeofday() in
    let ht = Hashtbl.create 91 in
    for k = 0 to n-1 do
      solve k n
	(fun b ->
	   if not (Hashtbl.mem ht b) then (
	     let b = Array.copy b in
	     List.iter
	       (fun b' ->
		  Hashtbl.add ht b' ()
	       )
	       (transformations b);
	     print b
	   )
	)
    done;
    let t1 = Unix.gettimeofday() in
    printf "Number solutions: %n\n%!" (Hashtbl.length ht / 8);
    printf "Time: %.3f\n%!" (t1-.t0)
end

My equivalent F#:

module Sequential =
  let run n =
    let timer = System.Diagnostics.Stopwatch.StartNew()
    let solve k =
      let sols = ResizeArray()
      solve k n (transformations >> Seq.min >> sols.Add)
      sols.ToArray()
    let sols =
      Array.init n solve
      |> Seq.concat
      |> Seq.distinct
      |> Seq.length
    printfn "Number solutions: %n" sols
    printfn "Time: %.3f" timer.Elapsed.TotalSeconds

Gerd's sequential OCaml run on his 4-core Opteron and my sequential F# run
on a 4-core W3520 have very similar performance characteristics.

Now for parallelization. Gerd's fastest parallel OCaml solution (aka MP2) is
287 lines long. In contrast, the F# can be parallelized by adding just 12
characters to the source code of the sequential implementation:

module Parallel =
  let run n =
    let timer = System.Diagnostics.Stopwatch.StartNew()
    let solve k =
      let sols = ResizeArray()
      solve k n (transformations >> Seq.min >> sols.Add)
      sols.ToArray()
    let sols =
      Array.Parallel.init n solve
      |> PSeq.concat
      |> PSeq.distinct
      |> PSeq.length
    printfn "Number solutions: %n" sols
    printfn "Time: %.3f" timer.Elapsed.TotalSeconds

I just replaced Array.init with Array.Parallel.init and Seq with PSeq.

Moreover, this trivially parallelized F# implementation also achieves
performance on this machine comparable to Gerd's parallel OCaml on his
machine. In particular, the absolute performance results for my parallel F#
are better in every single case. However, it is not clear how scalable these
parallel solutions are. On an 8-core E5405 Xeon I get only 5x speedup
compared to 3.8x speedup on 4 cores.

There can be little doubt that this solution is vastly more readable and
maintainable though.

-- 
Dr Jon Harrop, Flying Frog Consultancy Ltd.
http://www.ffconsultancy.com


             reply	other threads:[~2011-04-24 23:32 UTC|newest]

Thread overview: 5+ messages / expand[flat|nested]  mbox.gz  Atom feed  top
2011-04-24 23:32 Jon Harrop [this message]
2011-04-25 10:36 ` Gerd Stolpmann
2011-04-25 16:36   ` Frédéric Gava
2011-04-25 19:30     ` Jon Harrop
2011-04-25 23:33       ` Eray Ozkural

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