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Hi,

What is the most efficient way to calculate v^{T}Av where A is a CRS sparse matrix and v is a vector using Intel MKL (Fortran)?

Thanks in advance.

Carlos

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Dear customer,

The quadratic form x'*A*x is actually calculated as a sum of `n^2`

terms `A(i,j)*x(i)*x(j)`

, where `i`

and `j`

runs from `1`

to `n.`

Are you going to use CSR format for matrix A? If so, you could split the quadratic form into two equations. You could use mkl_?csrsymv to calculate y:=A*x first and then use ?dot to calculate sum of dot multiplication of two vectors res=x' * y. Hope it would be useful to you.

Best regards,

Fiona

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Hi,

Thanks for the reply, I was wondering if there was a built-in function for such calculation in MKL, thus my question.

Best regards

Carlos

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Dear customer,

I am afraid there might no real quadratic form function for matrix with sparse storage format. The good way is to separate calculation. Thanks.

Best regards,

Fiona

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