The Virtual Brain (TVB) is a large-scale brain simulator. With a community of thousands of users around the world, TVB has become a validated, popular and standard choice for the simulation of whole brain activity. TVB users can create simulations using neural mass models which can produce outputs for different analysis and modalities. TVB allows scientists to explore and analyze both simulated and experimental data. It contains analytic tools for evaluating relevant scientific parameters in light of that data. The current implementation of TVB is written in Python, with limited large-scale parallelization over different parameters. The objective of TVB-HPC is to enable large-scale parallelization of TVB simulations by making use of high performance computing to explore large parameter spaces for the models. With this approach, neuroscientists can define their models in a domain specific language based on NeuroML and automatically generate code which can run either on GPUs or on CPUs with different architectures and optimizations. The result is a framework that hides the complexity of writing robust parallel code and offers neuroscientists a fast and efficient access to high performance computing. TVB-HPC is publicly available on GitHub and, at the end of HBP project phase SGA2, it will be possible to launch large parameter simulations using code automatically generated with this framework via the HBP Collaboratory.