Here, we explore ways to a solution for this problem by investigating recent advances in generative modeling and present a study for the generation of events from a physical process with deep generative models. Simulating nature and in particular processes in particle physics require expensive computations and sometimes would take much longer than scientists can afford. We show simulation results at leading-order for multiple processes on different hardware configurations. Crucially, although only Leading Order is automatized, the library provides all ingredients necessary to build full complex Monte Carlo simulators in a modern, extensible and maintainable way. The package also provides an asynchronous unweighted events procedure to store simulation results. The simulation is performed using the VegasFlow and PDFFlow libraries which deploy automatically the full simulation on systems with different hardware acceleration capabilities, such as multi-threading CPU, single-GPU and multi-GPU setups. The exported code includes analytic expressions for matrix elements and phase space. In order to solve this challenge, we design a workflow and code library which provides to the user the possibility to simulate custom processes through the framework and a plugin for the generation and exporting of specialized code in a GPU-like format. The automation process of generating all the required components for MC simulation of a generic physics process and its deployment on hardware accelerator is still a big challenge nowadays. We present, a first general multi-purpose framework for Monte Carlo (MC) event simulation of particle physics processes designed to take full advantage of hardware accelerators, in particular, graphics processing units (GPUs).
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