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Beautiful Code by Andy Oram, Greg Wilson

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LAPACK DGETRF

As mentioned before, the introduction in the late 1970s and early 1980s of vector machines brought about the development of another variant of algorithms for dense linear algebra. This variant was centered on the multiplication of a matrix by a vector. These subroutines were meant to give improved performance over the dense linear algebra sub-routines in LINPACK, which were based on Level-1 BLAS. Later on, in the late 1980s and early 1990s, with the introduction of RISC-type microprocessors (the "killer micros") and other machines with cache-type memories, we saw the development of LAPACK Level-3 algorithms for dense linear algebra. A Level-3 code is typified by the main Level-3 BLAS, which, in this case, is matrix multiplication.

The original goal of the LAPACK project was to make the widely used LINPACK library run efficiently on vector and shared-memory parallel processors. On these machines, LIN-PACK is inefficient because its memory access patterns disregard the multilayered memory hierarchies of the machines, thereby spending too much time moving data instead of doing useful floating-point operations. LAPACK addresses this problem by reorganizing the algorithms to use block matrix operations, such as matrix multiplication, in the innermost loops (see the paper by E. Anderson and J. Dongarra listed under "Further Reading"). These block operations can be optimized for each architecture to account for its memory hierarchy, and so provide a transportable way to achieve ...

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