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From Xiangrui Meng <men...@gmail.com>
Subject Re: Using CUDA within Spark / boosting linear algebra
Date Fri, 03 Apr 2015 00:05:44 GMT
This is great! Thanks! -Xiangrui

On Wed, Apr 1, 2015 at 12:11 PM, Ulanov, Alexander
<alexander.ulanov@hp.com> wrote:
> FYI, I've added instructions to Netlib-java wiki, Sam added the link to them from the
project's readme.md
> https://github.com/fommil/netlib-java/wiki/NVBLAS
>
> Best regards, Alexander
> -----Original Message-----
> From: Xiangrui Meng [mailto:mengxr@gmail.com]
> Sent: Monday, March 30, 2015 2:43 PM
> To: Sean Owen
> Cc: Evan R. Sparks; Sam Halliday; dev@spark.apache.org; Ulanov, Alexander; jfcanny
> Subject: Re: Using CUDA within Spark / boosting linear algebra
>
> Hi Alex,
>
> Since it is non-trivial to make nvblas work with netlib-java, it would be great if you
can send the instructions to netlib-java as part of the README. Hopefully we don't need to
modify netlib-java code to use nvblas.
>
> Best,
> Xiangrui
>
> On Thu, Mar 26, 2015 at 9:54 AM, Sean Owen <sowen@cloudera.com> wrote:
>> The license issue is with libgfortran, rather than OpenBLAS.
>>
>> (FWIW I am going through the motions to get OpenBLAS set up by default
>> on CDH in the near future, and the hard part is just handling
>> libgfortran.)
>>
>> On Thu, Mar 26, 2015 at 4:07 PM, Evan R. Sparks <evan.sparks@gmail.com> wrote:
>>> Alright Sam - you are the expert here. If the GPL issues are
>>> unavoidable, that's fine - what is the exact bit of code that is GPL?
>>>
>>> The suggestion to use OpenBLAS is not to say it's the best option,
>>> but that it's a *free, reasonable default* for many users - keep in
>>> mind the most common deployment for Spark/MLlib is on 64-bit linux on EC2[1].
>>> Additionally, for many of the problems we're targeting, this
>>> reasonable default can provide a 1-2 orders of magnitude improvement
>>> in performance over the f2jblas implementation that netlib-java falls back on.
>>
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