How can I use BLAS/LAPACK to compute $$ B^{-1}AB^{-T} $$ where $A\in\mathbb{R}^{n,n}$, $B\in\mathbb{R}^{m,n}$ is full rank matrix with $m>n$, and $B^{-1}y:=\arg \min_{x} \|Bx-y\|_{2}$.

In theory, one could compute $$ B=QR $$ with orthogonal $Q\in\mathbb{R}^{m,n}$ and triagonal $R\in\mathbb{R}^{n,n}$ and then $$ R^{-1}Q^{T}AQR^{-T}. $$

However, I don't know how to implement this in BLAS/LAPACK (in C# if it matters). I haven't used either and the documentations don't help me at all. I found geqrf but have no idea what I should do with the outputs it gives me.

Alternatively: does anyone know of a widely available higher-level library that can do this for me in C#?

  • $\begingroup$ This would be relatively easy to implement in LAPACK, but "How do I do this in LAPACK?" questions by themselves are off-topic for this group. You could formulate this question by backing up and explaining the larger problem that you're working on. $\endgroup$ Sep 26, 2019 at 18:23
  • $\begingroup$ There’s an SO post about this: stackoverflow.com/questions/1437501/… $\endgroup$ Sep 27, 2019 at 7:55
  • $\begingroup$ @Amit I already have a Blast/Lapack library, but I don't know how to use it. I am used to numpy/scipy levels of abstraction $\endgroup$
    – Bananach
    Sep 27, 2019 at 8:12
  • $\begingroup$ Isn’t math.net, mentioned in the post, adequate? For example, for QR, you have this: collective2.com/c2explorer_help/html/… $\endgroup$ Sep 27, 2019 at 8:18
  • $\begingroup$ Or this: numerics.mathdotnet.com/api/… $\endgroup$ Sep 27, 2019 at 8:21

1 Answer 1


You should be able to do this efficiently using LAPACK/BLAS, using the QR factorization [geqrf], orthogonal multiplication [ormqr], and triangular solve [trsm] routines. LAPACK and BLAS place a lot of emphasis on economy of storage, so many of these algorithms operate in-place, overwriting their inputs with their outputs (geqrf, ormqr and trsm all work like this).

You should start off with geqrf, it will overwrite $\mathbf B$ with both $\mathbf Q$ and $\mathbf R$. The $\mathbf R$ output is just tabulated directly into the upper triangle, but $\mathbf Q$ is represented compactly in "reflector form". This representation requires a small/vector-sized amount of additional workspace ($\mathbf \tau$), empty storage that you provide to geqrf, that it will fill upon exit. You need to hang onto $\mathbf \tau$ to do anything else with $\mathbf Q$.

Because $\mathbf Q$ is stored in that special/reflector form, you can't just use BLAS/gemm to apply it. Instead you should use the LAPACK routine ormqr, it can apply $\mathbf Q$ to $\mathbf A$ from either the left or right and also apply transposition. It also operates inplace, overwriting $\mathbf A$ with (eg) $\mathbf Q^T \mathbf A$ or $\mathbf A \mathbf Q$. This can make it a little tricky to reason about, because (eg) $\mathbf Q^T \mathbf A$ and $\mathbf A$ are not necessarily the same size ($\mathbf Q$ being tall/skinny). Nevertheless you should be able to use two calls to ormqr (from the 'L'eft with a 'T'ranspose, then from the 'R'ight with 'N'otranspose) to get $\mathbf C = \mathbf Q^T\mathbf A\mathbf Q$ overwritten into the upper left corner of your original $\mathbf A$.

The last step, forming $\mathbf R ^{-1} \mathbf C \mathbf R^{-T}$ can be accomplished using the BLAS routine trsm. It applies the inverse of a triangular system, overwriting the input $\mathbf C$ with (eg) the output $\mathbf R^{-1} \mathbf C$. It can apply $\mathbf R$ from the left or right, and also apply a transposition to it. You'll need two calls, one from the 'L'eft with 'N'otranspose, then another from the 'R'ight with 'T'ranspose. In both cases you'll want to use uplo='U'pper because that's where geqrf stores $\mathbf R$.

Unfortunately I am not a C# expert, but I would imagine there's some usual way to call native/unmanaged "extern C" libraries, that's where you'd want to start.

  • $\begingroup$ Works perfectly. Just one more question. To accelerate the second call to ormqr I guess you should create a new array that contains only the first few matrix rows of the overwritten A (i.e. a new array that contains only Q^TA, nothing else) so that the call takes . Is there an elegant way to do this? $\endgroup$
    – Bananach
    Sep 27, 2019 at 12:20
  • $\begingroup$ Yes, you can/should do this. You don't even need to make a copy, you can just "slice" top(A) by adjusting the inputs to ormqr that specify the size/layout of A. [Specifically, top(A) has the same number of columns, leading dimension and data pointer as A, it just has fewer rows]. When implemented correctly, you should see that bottom(A) is untouched by the second call to ormqr. $\endgroup$ Sep 27, 2019 at 13:26
  • $\begingroup$ Are you sure this is also possible in a column major BLAS implementation? The top matrix isn't a contiguous block of memory in that case $\endgroup$
    – Bananach
    Oct 4, 2019 at 21:28
  • $\begingroup$ Yes, should be OK. You'll just need to adjust the rows/columns arguments but leave the leading dimension alone (since you have LD != rows, LAPACK will "jump" across the bottom parts of A) $\endgroup$ Oct 7, 2019 at 0:08

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