  The focus of my PhD thesis is on exploring parallel approaches to efficiently
solve problems modeled by constraints and presenting a new proposal. Current
solvers are very advanced; they are carefully designed to effectively manage
the high-level problems' description and include refined strategies to avoid
useless work. Despite this, finding a solution can take an unacceptable amount
of time. Parallelization can mitigate this problem when the instance of the
problem modeled is large, as it happens in real world problems. It is done by
propagating constraints in parallel and concurrently exploring different parts
of the search space. I am developing on a constraint solver that exploits the
many cores available on Graphics Processing Units (GPU) to speed up the search.
