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From Steven Buss <>
Subject Re: Current state of (dense) matrix multiplication?
Date Mon, 12 Apr 2010 04:27:22 GMT
If you're just doing matrix multiplication, I would advise that mahout
(or any mapreduce approach) isn't well suited to your problem. I did
the same computation with matlab (multiplying two 40k x 40k random
double precision dense matrices) using 14 cores and about 36GB of ram
on a single machine* and it finished in about 55 minutes. If I'm
reading your email correctly, you were working with 34*2*4=272 cores!
I'm not sure if dense matrix multiplication can actually be
efficiently mapreduced, but I am still a rookie so don't take my word
for it.

*The machine I am working on has 8 dual core AMD opteron 875s @ 2.2GHz
per core, with 64GB total system memory.

Steven Buss

On Sun, Apr 11, 2010 at 11:53 PM, Ted Dunning <> wrote:
> Vimal,
> We don't have any distributed dense multiplication operations because we
> have not yet found much application demand for distributed dense matrix
> multiplication.  Distributed sparse matrix operations are a big deal,
> however.
> If you are interested in working on the problem in the context of Mahout, we
> would love to help.  This is especially true if you have an application that
> needs dense operations and could benefit from some of the other capabilities
> in Mahout.
> On Sun, Apr 11, 2010 at 1:27 PM, Vimal Mathew <> wrote:
>> Hi,
>>  What's the current state of matrix-matrix multiplication in Mahout?
>> Are there any performance results available for large matrices?
>>  I have been working on a Hadoop-compatible distributed storage for
>> matrices. I can currently multiply two 40K x 40K dense double
>> precision matrices in around 1 hour using 34 systems (16GB RAM, two
>> Core2Quads' per node). I was wondering how this compares with Mahout.
>> Regards,
>>  Vimal

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