The design, development and staging of tests to certify liquid rocket engines usually require high-fidelity structural, fluid and thermal support analysis. These analyses are crucial to a successful engine test program since pressurization requirements, heat loads, cooling requirements and structural stresses are evaluated. Furthermore, these analyses are utilized to detect anomalies, unsteady pressure pulsations, structural vibrations, resonant modes and unexpected plume impingement zones that may be hazardous to the test stand structure and/or the test article. Such high-fidelity analyses have traditionally been performed on PC-cluster type computational platforms spanning over days/weeks given the complexity of the flowpath and flow regimes typically involved in the testing of liquid rocket engines. In this proposal we exploit the data parallelism of the computational algorithms involved to significantly enhance performance on low-cost high-speed GPU enabled hardware. Such a transition to GPU-based hardware will result in a paradigm shift for compute-intensive propulsion system applications from expensive CPU dominated PC-cluster architectures to economical workstation styled hybrid GPU-CPU systems, while resulting in dramatic decreases in turnaround times.