Abstract
AbstractThe goal of the LAPACK project is to design and implement a portable linear algebra library for etficient use on a variety of high‐performance computers. The library is based on the widely used LINPACK and EISPACK packages for solving linear equations, eigenvalue problems, and linear least‐squares problems, but extends their functionality in a number of ways. The major methodology for making the algorithms run faster is to restructure them to perform block matrix operations (e.g. matrix‐matrix multiplication) in their inner loops. These block operations may be optimized to exploit the memory hierarchy of a specific architecture. In particular, we discuss algorithms and benchmarks for the singular value decomposition.
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