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

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

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

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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

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

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

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

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