1. Modelling Languages Monadic Constraint Programming Benchmarks Future Work
Monadic Constraint Programming with Gecode
Pieter Wuille Tom Schrijvers
ModRef’09
Lisbon, September 20, 2009

2. Modelling Languages Monadic Constraint Programming Benchmarks Future Work
Modelling languages
Zinc approach Gecode approach
Separate language: Library for existing language:
Very declarative Boilerplate/function calls
Transferring data/results Directly callable/usable
Not all language features All host-language features

3. Modelling Languages Monadic Constraint Programming Benchmarks Future Work
Modelling languages
Zinc approach Gecode approach
Separate language: Library for existing language:
Very declarative Boilerplate/function calls
Transferring data/results Directly callable/usable
Not all language features All host-language features
MCP approach
Best of both worlds:
High-level abstractions
Very declarative
Directly usable
+ Compositional search transformers

4. Modelling Languages Monadic Constraint Programming Benchmarks Future Work
MCP Framework
MCP Framework
Constraint Solving framework for Haskell
Multiple solvers, variables, domains, search strategies, . . .
Fully functional, no side-effects
Solver states and search trees are first-class data
Defines common syntactic sugar

5. Modelling Languages Monadic Constraint Programming Benchmarks Future Work
FD-MCP: FD solving for MCP
FD-MCP: Common FD Infrastructure
FD syntax for term and constraint language
Model optimizations and decompositions
Multiple solver backends

6. Modelling Languages Monadic Constraint Programming Benchmarks Future Work
FD-MCP: FD solving for MCP: example
model :: FDModel
model =
exist 4 $ list@[a,b,c,d] ->
list ‘allin‘ (0,711) /
sorted list /
a + b + c + d @= 711 /
a * b * c * d @= 711*100*100*100 /
return list
main = example_main_void model

7. Modelling Languages Monadic Constraint Programming Benchmarks Future Work
FD-MCP: Solvers
FD Solvers
Haskell-only solver
Pseudo-solver that generates C++ code for Gecode
new Real solver using Gecode propagation
new Real solver using Gecode search+propagation

8. Modelling Languages Monadic Constraint Programming Benchmarks Future Work
Benchmark: Allinterval
Benchmark allinterval
1000
C++ Gecode
MCP Generated C++
100
MCP using Gecode prop
MCP using Gecode prop+search
10 MCP Haskell
1
time (s)
0.1
0.01
0.001
0.0001
1e-05
2 4 6 8 10 12 14 16
problem size

9. Modelling Languages Monadic Constraint Programming Benchmarks Future Work
Benchmark: Partition
Benchmark partition
1000
C++ Gecode
MCP Generated C++
100 MCP using Gecode prop
MCP using Gecode prop+search
MCP Haskell
10
1
time (s)
0.1
0.01
0.001
0.0001
4 6 8 10 12 14 16 18 20
problem size

10. Modelling Languages Monadic Constraint Programming Benchmarks Future Work
Future Work
Future work
More benchmarks
Improve performance of MCP using Gecode propagation
Parametrized models, loop constructs, reification, . . .
More backends, constraints, variable types, . . .
Optimizations, generalizations
Concurrency

11. Modelling Languages Monadic Constraint Programming Benchmarks Future Work
Thank you!
Questions?
Further reading:
Monadic Constraint Programming,
T. Schrijvers, P. Stuckey, P. Wadler.
Journal of Functional Programming – to appear.
More information:
Source code, papers, . . .
http://www.cs.kuleuven.be/~pieterw/site.php/Topics/FDMCP