From Newsgroup: comp.lang.javascript


We recently presented a fast constraint solver
termed Railgun CLP(FD) that modelled attributed
variables simply via ‘$ATTR’/2 compounds and could
deal with integer dif/2 constraints. In this
instalment we allow (#\=)2 constraints and demonstrate
that it can be ported to SWI-Prolog.

Using polyfill for ‘$SEQ’/2 from Dogelog Player,
we observed that running Railgun CLP(FD) inside
SWI-Prolog gives a 2–3x speed-up for the Queens
example, on both 32-bit and 64-bit. On the other
hand the price tag for big integer flexibility
seems to be a factor 35x slow down.

See also:

Porting Railgun CLP(FD) to SWI-Prolog
https://medium.com/2989/e9f2ef4e6878

Mild Shock schrieb:

Hi,

Many existing and evolving constraint logic
programming projects resemble some ancient
invention of gunpowder. For example SWI-Prologs
9.3.35 corouting for delayed goals is mainly
based on unify hooks. We show how verify hooks,
already used in formerly Jekejeke Prolog, can
be braught to Dogelog Player in a 100% Prolog fashion.

Since the recent version of Dogelog Player
supports cyclic terms, we could let the Jini
out of the bottle, and provide the experimental
library(edge/railgun) to model delayed goals with
nothing else than Alain Colmerauers rational trees.
The result is a Lean CLP of ca. 100 lines of code,
that already provides a simple constraint (#\=)/2
and a global constraint all_different/1.

The results are encouraging. For problems that
are not over constrained, Dogelog Player leaves
existing Prolog systems clearly behind, showing
a 2-3x times speed-up against SWI-Prolog and a
20-30x times speed-up against Trealla Prolog.
For more constrained problems we suggest ommiting
forward checking in favor of a form of ahead of
time (AOT) variable ordering. With this approach
and for Sudoku problems we are then in the midfield
between SWI-Prolog and Trealla Prolog.

Bye

See also:

Lean CLP for Dogelog Player https://qiita.com/j4n_bur53/items/addf1fc86856dd682dcb

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From Newsgroup: comp.lang.javascript


We recently presented a fast constraint solver
termed Railgun CLP(FD) that modelled attributed
variables simply via ‘$ATTR’/2 compounds. We
already went through an iteration which allowed
(#\=)/2 constraints. In this instalment we
present some further progress. In particular we
intoduce a discount(C) = 1/k heuristic.

We demonstrated an additional scoring of variables
among the same degree to improve the static variable
ordering (SVO). It can give a 100x times speed up
in a magic square example. Putting Dogelog Player
on equal foot with SWI and ECLiPSe, while recent
versions of Scryer and Trealla were still 10x-30x
times slower.

See also:

Supersonic FF for Railgun CLP(FD) https://qiita.com/j4n_bur53/items/0d1334f1f4c2234f3f47

Mild Shock schrieb:

We recently presented a fast constraint solver
termed Railgun CLP(FD) that modelled attributed
variables simply via ‘$ATTR’/2 compounds and could
deal with integer dif/2 constraints. In this
instalment we allow (#\=)2 constraints and demonstrate
that it can be ported to SWI-Prolog.

Using polyfill for ‘$SEQ’/2 from Dogelog Player,
we observed that running Railgun CLP(FD) inside
SWI-Prolog gives a 2–3x speed-up for the Queens
example, on both 32-bit and 64-bit. On the other
hand the price tag for big integer flexibility
seems to be a factor 35x slow down.

See also:

Porting Railgun CLP(FD) to SWI-Prolog
https://medium.com/2989/e9f2ef4e6878

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