Linear Algebra using Extensible Database Technology
Computational models of the real world often involve analyzing discrete points of data logically represented as matrices. Such real-world models are produced in a large number of disciplines, including science and engineering. The calculations on these models can be computationally intensive since the data set is usually large. Nowadays most data is stored in database management systems without the matrix support rich computational models require. In this thesis I describe how I adapted an object-relational database management system to store, model and perform calculations on matrices of varying types.
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