Network virtualization is widely regarded as a key technology for the Future Internet, enabling the deployment of new network protocols without changing dissimilar hardware devices. This leads to the problem of mapping virtual demands to physical resources, known as Virtual Network Embedding (VNE). Current VNE algorithms do not scale with respect to the substrate network size. Therefore, these algorithms are not applicable in large-scale scenarios where virtual networks have to be embedded in a timely manner.This paper discusses DPVNE, a Distributed and Generic VNE framework: It runs cost-oriented centralized embedding algorithms in a distributed way, spreading workload across the substrate network instead of concentrating it on one single node (as centralized algorithms do). Several state-of-the-art algorithms were evaluated running inside the DPVNE framework. Results show that DPVNE leads to runtime improvements in large-scale scenarios and embedding results are kept comparable.