Re: [eigen] Matrix decompositions |

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*To*: eigen <eigen@xxxxxxxxxxxxxxxxxxx>*Subject*: Re: [eigen] Matrix decompositions*From*: Sameer Agarwal <sameeragarwal@xxxxxxxxxx>*Date*: Thu, 28 Feb 2013 13:00:52 -0800*Dkim-signature*: v=1; a=rsa-sha256; c=relaxed/relaxed; d=google.com; s=20120113; h=mime-version:x-received:in-reply-to:references:date:message-id :subject:from:to:content-type; bh=TtVoSWkL8nIw0UXiNkt5pJ99pI/7Cc0AoujsNULwaR4=; b=k2OOhWDJnjudSIdl3FHOB3iIontcHBNnihplxWwjdxLlPq45jgLj+W261DGlaZPRLg OO2zmr6PArcCHLtCppxvatk8VJptnWVtwE0QSbvs37uMZuNPiWJy/s/PffqRCvZcjbEj bVfD5k/ojZDsdjopejmleNVZfZBacOkkRuCzTXxvI/6LjsjW+avc4zXtsdVsTlFDpSbx leiN5LdwHuGr99FcxSrXXj5MeL6S1RgRpvq8VyQIr1u6gbLtdAwMS5R2mXA0aIW6uJtW wKUHtYJvh1hkceinSXM9b7fYJNjFgbOc0sU4c2+f4iPdNPkNTQd4jnHpLDkpj2D2ApTR MhDg==

Thanks Gael,

> 1. What if any impact does the row/column major storage have on the variousFor Cholesky and LU, the storage order should not matter much, for QR,

> matrix decomposition algorithms in Eigen? I imagine, that QR factorization

> for example will do better if the storage is column major.

a column major storage is clearly preferable.

Great.

Yes, the factorizations do exploit SIMD, but no, the alignement does

> 2. Are the matrix decomposition algorithms affected by the alignment of the

> underlying storage, or more generally, do the matrix decompositions use SIMD

> vectorization which in turns require alignment of the underlying data?

not matter. This is because such algorithms work on sub matrices which

are not aligned even if the (0,0) coeff is.

So why is SIMD/vectorization disabled on unaligned matrices? and by turn on Map objects.

Sameer

gael

> In this case I did do some benchmarking, where I used an eigen Matrix and a

> block of memory allocated using new and wrapped inside a Map object, and

> performed cholesky factorization on numerically identical (row major

> matrices) and did not notice any difference. Thus the curiosity. It is

> entirely possible that my benchmark is broken.

>

> Thanks,

> Sameer

>

**Follow-Ups**:**Re: [eigen] Matrix decompositions***From:*Gael Guennebaud

**References**:**[eigen] Matrix decompositions***From:*Sameer Agarwal

**Re: [eigen] Matrix decompositions***From:*Gael Guennebaud

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