Re: [eigen] first benchmark of large and sparse matrix |

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*To*: eigen@xxxxxxxxxxxxxxxxxxx*Subject*: Re: [eigen] first benchmark of large and sparse matrix*From*: "Gael Guennebaud" <gael.guennebaud@xxxxxxxxx>*Date*: Mon, 23 Jun 2008 11:00:36 +0200*Dkim-signature*: v=1; a=rsa-sha256; c=relaxed/relaxed; d=gmail.com; s=gamma; h=domainkey-signature:received:received:message-id:date:from:to :subject:in-reply-to:mime-version:content-type :content-transfer-encoding:content-disposition:references; bh=rE+akfTZGKp1dn51LFIX/HZ+GqYJ4LXn256AV1xzXuY=; b=EtT0GrTTw7mBVHx9fcOzkHxoBr5Q9/VExQgdWEYop174Xtu5LHJrLBNGl9F9YBYDhC GTCXgX9A77dEFXlev1cgcut5IiNOEdGvkovxApjOtuQSzVnNzoAml9aIOgPWTmthcKOo 04b9lZ9BJXHa9wQ+dVEU+Q6w/qBoBAUNUlNrA=*Domainkey-signature*: a=rsa-sha1; c=nofws; d=gmail.com; s=gamma; h=message-id:date:from:to:subject:in-reply-to:mime-version :content-type:content-transfer-encoding:content-disposition :references; b=g9xvcvpdGO8WCvLX3FPUCP0PRh27BrnJehv3Zcfk03I12lsFCOZVm5bmygmcYVY+Dx 7Y24IIxafREB446QcY1X0Pm+/hVcgFMISoVHybeuisnPwNfppZsNiOeq4szucda7bv0O /sYE1Q6eKSWPcPf2HdCqHkqfbWn+OyQpO2lHU=

On Mon, Jun 23, 2008 at 10:38 AM, Benoît Jacob <jacob@xxxxxxxxxxxxxxx> wrote: > On Monday 23 June 2008 10:13:37 Gael Guennebaud wrote: >> On Mon, Jun 23, 2008 at 7:30 AM, Benoît Jacob <jacob@xxxxxxxxxxxxxxx> wrote: >> > On Monday 23 June 2008 07:05:30 Benoît Jacob wrote: >> >> this is of high interest for Krita and for Step and probably has >> >> countless interesting applications >> > >> > I forgot to mention that support for sparse matrices should be of high >> > interest to OpenBabel (chemistry lib, also considering eigen2): if I >> > remember well they sometimes apply solving algorithms to the adjacency >> > matrix of a molecule, so for a molecule with N atoms the matrix is NxN >> > and has 2N nonzero entries. As far as I remember they used to apply dense >> > algorithms, so N^3 complexity which is only doable for small N (like >> > 10^2) while some molecules they deal with have up to 10^5 atoms. >> >> hm... if there are only 2N nonzero entries then using a sparse matrix >> is pointless: > > I don't know much about sparse matrices, I believed that the less nonzero > entries the more sense it made to use a sparse matrix. > >> the overhead is one int per nonzero entry. > > Precisely, since there are few nonzero entries, this is acceptable! arf sorry sorry I read "2N zero entries" and then I wrote "2N nonzero entries" but in my mind it was still "2N zero entries"..... next time I'll wait to be really awake, so forget what I said.... a sparse matrix is perfect for that ! > > Indeed, if the entries are only 0 and 1 then it is not optimal to store as a > sparse matrix, but still, that is already quite good and far better than > dense storage; moreover, I don't know if chemists do that, but at least in > math it's useful to work with adjacency matrices of graphs with arbitrary > values associated to graph edges, so in this case it's really a sparse > matrix. yes yes sure, with 2N non zero entries it's really sparse. Acually I was surprised that the corresponding matrix was so dense, so I though the graph also included collision constraints or whatever else.... > >> Also, I think it's very important to support natively linear system >> solvers as I know many users would never accept a dependency on >> another lib.... especially if this lib depends itself on lapack that >> is the case of most of them. > > OK. Let's see if we can use GMM++ code: GMM++ is LGPL 2.1-or-later. > > http://www.gnu.org/licenses/gpl-faq.html#AllCompatibility > > - normally, we can't copy and paste their code > - but we can write to the author, he's cool > - or we can ship some GMM++ code in separate files, without relicensing. hm... it looks like things are worse because most of the algo provided in GMM++ comes from ITL, which is not LGPL, it is a custom one which is more like GPL (non commercial use) : http://www.osl.iu.edu/research/itl/LICENSE.php3 gael.

**References**:**[eigen] first benchmark of large and sparse matrix***From:*Gael Guennebaud

**Re: [eigen] first benchmark of large and sparse matrix***From:*Benoît Jacob

**Re: [eigen] first benchmark of large and sparse matrix***From:*Gael Guennebaud

**Re: [eigen] first benchmark of large and sparse matrix***From:*Benoît Jacob

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