Abstract : With the emergence of highly heterogeneous, dynamic and large distributed platforms, declarative programming, whose goal is to ease the programmer's task by separating the control from the logic of a computation, has regained a lot of interest recently, as a means of programming such platforms. In particular, rule-based programming, which allows to simply specify crucial features such as communication protocols or computing workflows, is regarded as a promising model in this quest for adequate programming abstractions for these platforms. However, while these models are gaining a lot of attention, there is a demand for generic tools able to run such models at large scale. The chemical programming model, which was designed following the chemical metaphor, is a rule-based programming model, with a non-deterministic execution specification, where rules are applied concurrently, on a multiset of objects. In this paper, we explore the experimental side of concurrent rule-based models, by deploying a distributed chemical runtime at large scale. The architecture proposed combines a peer-to-peer communication layer with an adaptive protocol to atomically capture objects on which rules should be applied, and an efficient termination detection scheme. We describe the software prototype fully implementing this architecture. Based on its deployment over a large real-world test-bed, we present its performance results, which confirm analytically obtained complexities, and experimentally show the sustainability of such a programming model.