- FactorizationQR
- FactorizationQRNonNeg
- FactorizationQRPivot
- FactorizationQRTallSkinny
- FactorizationLQ
- FactorizationLQShortWide
- FactorizationQL
- FactorizationRQ
- FactorizationRZ
- FactorizationQR2
- FactorizationRQ2
FactorizationLQShortWide
Computes a blocked Short-Wide LQ factorization of an m-by-n (m<n) matrix: A = L * Q. LAPACK function LASWLQ.
Computing for type matrix<double>
bool matrix::FactorizationLQShortWide(
|
Computing for type matrix<float>
bool matrix::FactorizationLQShortWide(
|
Computing for type matrix<complex>
bool matrix::FactorizationLQShortWide(
|
Computing for type matrix<complexf>
bool matrix::FactorizationLQShortWide(
|
Parameters
reduced
[in] Calculation mode. If reduced is true then matrices L, Q calculated with reduced dimensions (M, K), (K, N). If reduced is false it means complete calculation of matrices L, Q with dimensions (M,N), (N,N).
mb
[in,out] The row block size to be used in the blocked LQ. M >= MB >= 1. If 0 is passed in the parameter, the optimal MB value will be calculated using the ILAENV function and returned.
nb
[in,out] The column block size to be used in the blocked LQ. NB > M. If 0 is passed in the parameter, the optimal NB value will be calculated using the ILAENV function and returned.
L
[out] Lower triangular matrix L.
Q
[out] Orthogonal or unitary matrix Q.
Return Value
Return true if successful, otherwise false in case of an error.
Note
If reduced is true, matrix L is of m-by-m sizes, matrix Q is of m-by-n sizes.
If reduced is false, matrix L is of m-by-n sizes, matrix Q is of n-by-n sizes.
Although the LAPACK routine ILAENV computes suitable values for MB and NB automatically, these parameters can be tuned manually to match the CPU cache size, which may provide a significant performance improvement. A useful rule of thumb is:
MB = min(M, 32 or 64 or 128)
NB = max(2*M, cache_bytes / (sizeof(type)*M))
NB = max(NB, M + MB)
NB = min(NB, N-1)