The problem of ontology alignment is prominent for applica- tions that operate on integrated semantic data. With ontologies becom- ing numerous and increasingly large in size, scalability is an important issue for alignment tools. This work introduces a novel approach for computing ontology alignments using cloud infrastructures. An align- ment algorithm based on particle swarm optimisation is deployed on a cloud infrastructure, taking advantage of its ability to harness parallel computation resources. The deployment is done with a focus on parallel efficiency, taking into account both communication latency and compu- tational inhomogeneity among parallel execution units. Complementing previous experiments showing the effectiveness of the alignment algo- rithm, this paper contributes an experiment executed “in the cloud”, which demonstrates the scalability of the approach by aligning two large ontologies from the biomedical domain.