Simulations of frames from existing and upcoming high-resolution spectrographs, targeted for high accuracy radial velocity measurements, are computationally demanding (both in time and space). We present in this paper an innovative approach based on both parallelization and distribution of the workload. By using NVIDIA CUDA custom-made kernels and state-of-the-art cloud-computing architectures in a Platform as a Service (PaaS) approach, we implemented a modular and scalable end-to-end simulator that is able to render synthetic frames with an accuracy of the order of few cm/sec, while keeping the computational time low. We applied our approach to two spectrographs. For VLT-ESPRESSO we give a sound comparison between the actual data and the simulations showing the obtained spectral formats and the recovered instrumental profile. We also simulate data for the upcoming HIRES at the ELT and investigate the overall performance in terms of computational time and scalability against the size of the problem. In addition we demonstrate the interface with data-reduction systems and we preliminary show that the data can be reduced successfully by existing methods.
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