Abstract: Real-time ray tracing is an important tool in computational research. Among other things, it is used to model sensors for autonomous vehicle simulation, efficiently simulate radiative energy propagation, and create effective data visualizations. However, raytracing libraries currently offered for GPU platforms have a high level of complexity to facilitate the detailed configuration needed by gaming engines and high-fidelity renderers. A researcher wishing to take advantage of the performance gains offered by the GPU for simple ray casting routines would need to learn how to use these ray tracing libraries. Additionally, they would have to adapt this code to each GPU platform they run on. Therefore, a C++ API has been developed that exposes simple ray casting endpoints that are implemented in GPU-specific code for several contemporary device platforms. This API currently supports the NVIDIA OptiX ray tracing library, Vulkan, AMD Radeon Rays, and even Intel Embree. Benchmarking tests using this API provide insight to help users determine the optimal backend library to select for their ray tracing needs. HPC research will be well-served by the ability to perform general purpose raytracing on the increasing amount of graphics and machine learning nodes offered by the DoD High Performance Computing Modernization Program.