Level 2: matrix-vector operations, O(n^2) work

Matrix operations that perform \( O(n^2) \) work on \( O(n^2) \) data. These are memory bound, since every operation requires a memory read or write. More...

Modules
	geadd: Add matrices
	\( B = \alpha A + \beta B \)
	gemv: General matrix-vector multiply
	\( y = \alpha Ax + \beta y \)
	ger: General matrix rank 1 update
	\( A = \alpha xy^T + A \)
	hemv: Hermitian matrix-vector multiply
	\( y = \alpha Ax + \beta y \)
	her: Hermitian rank 1 update
	\( A = \alpha xx^T + A \)
	her2: Hermitian rank 2 update
	\( A = \alpha xy^T + \alpha yx^T + A \)
	symv: Symmetric matrix-vector multiply
	\( y = \alpha Ax + \beta y \)
	syr: Symmetric rank 1 update
	\( A = \alpha xx^T + A \)
	syr2: Symmetric rank 2 update
	\( A = \alpha xy^T + \alpha yx^T + A \)
	trmv: Triangular matrix-vector multiply
	\( x = Ax \)
	trsv: Triangular matrix-vector solve
	\( x = op(A^{-1})\; b \)
	lacpy: Copy matrix
	\( B = A \)
	lascl: Scale matrix by scalar
	\( A = \alpha A \)
	lascl2: Scale matrix by diagonal
	\( A = D A \)
	laset: Set matrix to constants
	\( A_{ij} = \) diag if \( i=j \); \( A_{ij} = \) offdiag otherwise.

Detailed Description

Matrix operations that perform \( O(n^2) \) work on \( O(n^2) \) data. These are memory bound, since every operation requires a memory read or write.