[gecode-users] Does Gecode compile to constraint-free code?

[Christian Schulte]

Hi,

I am not sure that I get your question. For realistic constraints such as
those available in Gecode this is not really possible. Warwick's paper talks
about a slightly different setup (solving very simple [linear] constraints
repeatedly).

Why not just try to resolve using Gecode?

Christian

--
Christian Schulte, www.ict.kth.se/~cschulte/



-----Original Message-----
From: users-bounces at gecode.org [mailto:users-bounces at gecode.org] On Behalf
Of Maik Riechert
Sent: Monday, August 27, 2012 10:06 PM
To: users at gecode.org
Subject: [gecode-users] Does Gecode compile to constraint-free code?

Hi all,

I'm quite new to the whole space of constraint programming and have recently
made use of a finite domain constraint solving framework called monadiccp
[1] for one of my current projects [2]. I measured the performance and saw
that it was ~800x slower than my direct constraint-free implementation.

The framework also supports Gecode (apart from a pure Haskell
implementation) but after seeing this slowdown I haven't tested it yet as
the C-to-Haskell interfacing probabably also produces some overhead and I
doubt it can get really fast.

I came across the paper "Compiling Constraint Solving using Projection" 
from Harvey et al [3] which I find quite promising. In my particular case I
have very few (at the moment two) constraint systems which need to be solved
thousands of times. They have 10-20 constraints and vary only in their input
arguments, i.e. the constraints itself stay the same.

As the solver I use is a runtime solver which reads/simplifies/solves the
whole system over and over, it is slow. The question is: Could the approach
of the paper be used to derive constraint-free equations *once* and then use
those in the actual algorithm? And does Gecode maybe support that already?

Cheers
Maik

[1] http://hackage.haskell.org/package/monadiccp/
[2]
https://github.com/neothemachine/adp-multi/blob/master/src/ADP/Multi/Rewriti
ng/ConstraintSolver.hs#L213
[3]
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.17.3194&rep=rep1&ty
pe=pdf

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