Modern computational accelerator technologies like FPGAs and GPUs can be difficult to program efficiently and effectively due to the complex nature of the underlying hardware. Many companies provide libraries with highly specialized algorithms that can be accessed from compiled languages like C/C++/Fortran. However, this presents another barrier for many scientists who generally program in high-level languages like MATLAB and IDL. The tools developed in this project, can make these computational accelerators easily accessible to a much wider range of scientists through open source high level languages. The software tools in this project can benefit a variety of current NASA missions including the Landsat Continuity Mission (LDCM), or planned missions like HyspIRI, the hyperspectral infrared imager. These missions offer a glimpse of the flood of data that is going to be expected from far-future missions. This is not only a challenge encountered with Earth Science missions, but with all future missions, including the Solar Dynamics Observatory or the James Webb Space Telescope. Mechanisms currently used or investigated to reduce the amount of data prior to transmission to Earth ranges from fairly simple trigger functions as encountered on board of RHESSI or planned for XMM, to more complex cloud detector algorithms on board the Earth Observing System (EOS) mission.