Modern scientific enterprises generate enormous volumes of data, as many scientific fields have transitioned from being data poor to data rich recently. To make sense of this data, the scientific enterprise relies on new computational methods and computing infrastructure to realize new insights. In other words, the computational methods used for large scale data analysis are now tools of the scientific community as they are central to the knowledge generation process. This project aims to address a major limitation in large scale data analysis by designing and implementing novel methods that employ computational storage devices, which combine the storage inside of a computer with a configurable processor that resides on the storage device itself. This project will yield new insights into the efficient use of these computational storage devices and will demonstrate how they can be used to remedy the challenges faced in several scientific domains. The project will benefit society by training students in the use of cutting edge technologies that are of national importance and which have great potential to bolster the U.S. economy. Computational storage devices are an emerging technology for accelerating large scale data intensive computations because they combine storage with field programmable gate arrays. Relocating computational tasks from the host processor to a computational storage device eliminates data movement between the computational storage device and the central