is there a MKL API for this use-case? R^TRx=b

[Azua_Garcia__Giovann]

Hello,

I need to solve efficiently R^TRx=b where R is upper triangular. I cover this use-case doing two solve steps:

R^Ty=b,

Rx=y

and this works OK. However, I wonder whether there is a more efficient LAPACK or MKL API to solve the entire R^TRx=b at once.

Many TIA,

Best regards,

Giovanni

[Alexander_K_Intel2]

Hi, Just a few questions - are your matrix sparse or dense? And how you prepare this matrix - using MKL functionality or not? With best regards, Alexander Kalinkin

[Azua_Garcia__Giovann]

Hi Alexander, The matrix is dense and upper triangular R. R is the result of up-dating and down-dating a Cholesky decomposition done as a series of incremental updates and not using MKL. However, the lower triangular is zero. Best regards, Giovanni

[Alexander_K_Intel2]

Hi, You can solve your system by 2 call of dtrsv function. Is it suitable for you or you want to solve your equation by one call? With best regards, Alexander Kalinkin

[Azua_Garcia__Giovann]

Hi Alexander, Exactly. My question is, is there a better way than making 2 calls of the dtrsv function. Or in other words, is it possible to solve R^TRx=b in one step. Thanks in advance, Best regards, Giovanni