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tracyx

New Contributor I

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02-15-2012
05:09 PM

263 Views

evaluating matrix quadratic form

Thanks, Tracy

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mecej4

Black Belt

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02-15-2012
08:45 PM

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For dense A, a call to **?gemv** to compute A X, followed by a call to **?dot**.

Royi

Novice

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04-26-2019
09:46 AM

263 Views

The result of:

X' * A * X

For symmetric A has such a nice structure (Result is symmetric) that it is a pity MKL doesn't have an optimized function for it.

Quadratic Forms are very common in Machine Learning, Optimization, etc... It would benefit many users.

Spencer_P_Intel

Employee

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04-26-2019
01:44 PM

263 Views

In case of dense, there is no single call solution as mecej4 mentioned.

However, if X and A are sparse matrices, then we added exactly this type of product to our Inspector-Executor Sparse BLAS routines. The structure is indeed quite nice. This type of product shows up a lot in multi-scale finite element methods as well where X could be a projection or elongation matrix. We call it the symmetric product with api -- mkl_sparse_sypr().

See reference documentation mkl_sparse_sypr for more details on how to use it.

Sigolaev__Yuriy

Beginner

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04-28-2019
04:27 PM

263 Views

Blas Level 2 is a tricky thing. For example, my dsptrd faster dsptrd Intel MKL twice.

See https://software.intel.com/en-us/forums/intel-math-kernel-library/topic/288316

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For more complete information about compiler optimizations, see our Optimization Notice.