Concepts inUsing dense storage to solve small sparse linear systems
Memory footprint
Memory footprint refers to the amount of main memory that a program uses or references while running. This includes all sorts of active memory regions like code, static data sections (both initialized and uninitialized), heap, as well as all the stacks, plus memory required to hold any additional data structures, such as symbol tables, constant tables, debugging structures, open files, etc, that the program ever needs while executing and will be loaded at least once during the entire run.
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Data structure
In computer science, a data structure is a particular way of storing and organizing data in a computer so that it can be used efficiently. Different kinds of data structures are suited to different kinds of applications, and some are highly specialized to specific tasks. For example, B-trees are particularly well-suited for implementation of databases, while compiler implementations usually use hash tables to look up identifiers.
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Linear equation
A linear equation is an algebraic equation in which each term is either a constant or the product of a constant and (the first power of) a single variable. Linear equations can have one or more variables. Linear equations occur with great regularity in applied mathematics.
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Equation
An equation is a mathematical statement that asserts the equality of two expressions. In modern notation, this is written by placing the expressions on either side of an equals sign (=), for example asserts that x+3 is equal to 5. The = symbol was invented by Robert Recorde (1510�), who considered that nothing could be more equal than parallel straight lines with the same length.
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Computer performance
Computer performance is characterized by the amount of useful work accomplished by a computer system compared to the time and resources used.
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Sparse matrix
In the subfield of numerical analysis, a sparse matrix is a matrix populated primarily with zeros. The term itself was coined by Harry M. Markowitz. Conceptually, sparsity corresponds to systems which are loosely coupled. Consider a line of balls connected by springs from one to the next; this is a sparse system. By contrast, if the same line of balls had springs connecting each ball to all other balls, the system would be represented by a dense matrix.
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