The real-world testing of robotic and autonomous vehicles faces many challenges including: safety; feasibility; effectiveness; expense; and timeliness. The development of high performance computing has created innumerable opportunities for effectively and efficiently processing large data sets. These data sets can range from modeling and simulation scenarios to the vast amounts of complex data being gathered by unmanned vehicles. In all cases, the data needs to be stored, managed, and processed to have usable information to drive smart decision making. Leveraging high performance computing to more efficiently, effectively, and economically conduct robotic and autonomous vehicle testing in a virtual environment is a logical step. Consequently, TARDEC has developed a real-time modeling and simulation capability to test and evaluate autonomy solutions while RAVE has designed and developed a specialized high performance computing system for TARDEC to support this capability.