Hi all.

I'm writing to you to ask for advice or a hint to the right direction.

In our department, more and more researchers ask us (IT administrators)
to assemble (or to buy) GPGPU powered workstations to do parallel computing.

As I already manage a small CPU cluster (resources managed using SGE),
with my boss we talked about building a new GPU cluster. The problem is
that I have no experience at all with GPU clusters.

Apart from the already running GPU workstations, we already have some
new HW that looks promising to me as a starting point for a GPU cluster.

- 1x Dell PowerEdge R720
- 1x Dell PowerEdge C410x
- 1x NVIDIA M2090 PCIe x16
- 1x NVIDIA iPASS Cable Kit
(Dell forgot to include the iPASS adapter for the R720!! :-D)

I'd be grateful if you could kindly give me some advice and/or hint to
the right direction.

In particular I'm interested on your opinion on:
1) is the above HW suitable for a small (2 to 4/6 GPUs) GPU cluster?
2) is apache adhoop suitable (or what could we use?) as a queuing and
resource management system? We would like the cluster to be usable by
many users at once in a way that no user has to worry about resources,
just like we do on the CPU cluster with SGE.
3) What distribution of linux would be more appropriate?
4) necessary stack of sw? (cuda, hadoop, other?)

Thank you very much for your valuable insight!

Best regards.
Robi

Hadoop streaming can do this, and there's been some discussion in the past,
but it's not a core use case. Check the list archives.

Russell Jurney http://datasyndrome.com

On Jan 17, 2013, at 9:25 AM, Jeremy Lewi <[EMAIL PROTECTED]> wrote:

I don't think running hadoop on a GPU cluster is a common use case; the
types of workloads for a hadoop vs. gpu cluster are very different although
a quick google search did turn up some. So this is probably not the best
mailing list for your question.

J
On Thu, Jan 17, 2013 at 5:18 AM, Roberto Nunnari
<[EMAIL PROTECTED]>wrote:

> Roberto Nunnari wrote:
>
>> Hi all.
>>
>> I'm writing to you to ask for advice or a hint to the right direction.
>>
>> In our department, more and more researchers ask us (IT administrators)
>> to assemble (or to buy) GPGPU powered workstations to do parallel computing.
>>
>> As I already manage a small CPU cluster (resources managed using SGE),
>> with my boss we talked about building a new GPU cluster. The problem is
>> that I have no experience at all with GPU clusters.
>>
>> Apart from the already running GPU workstations, we already have some new
>> HW that looks promising to me as a starting point for a GPU cluster.
>>
>> - 1x Dell PowerEdge R720
>> - 1x Dell PowerEdge C410x
>> - 1x NVIDIA M2090 PCIe x16
>> - 1x NVIDIA iPASS Cable Kit
>> (Dell forgot to include the iPASS adapter for the R720!! :-D)
>>
>> I'd be grateful if you could kindly give me some advice and/or hint to
>> the right direction.
>>
>> In particular I'm interested on your opinion on:
>> 1) is the above HW suitable for a small (2 to 4/6 GPUs) GPU cluster?
>> 2) is apache adhoop suitable (or what could we use?) as a queuing and
>> resource management system? We would like the cluster to be usable by many
>> users at once in a way that no user has to worry about resources, just like
>> we do on the CPU cluster with SGE.
>> 3) What distribution of linux would be more appropriate?
>> 4) necessary stack of sw? (cuda, hadoop, other?)
>>
>> Thank you very much for your valuable insight!
>>
>> Best regards.
>> Robi
>>
>
> Anybody on this, please?
> Robi
>
>

I've seen some academic researches on this direction, with good results.
Some computations can be expressed by GPGPU, but it is still a restrict
number of cases. If is not easy to solve problems using MapReduce, solve
some problems with SIMD is harder.

--
Thiago Vieira
On Thu, Jan 17, 2013 at 9:24 PM, Russell Jurney <[EMAIL PROTECTED]>wrote:

> Hadoop streaming can do this, and there's been some discussion in the
> past, but it's not a core use case. Check the list archives.
>
> Russell Jurney http://datasyndrome.com
>
> On Jan 17, 2013, at 9:25 AM, Jeremy Lewi <[EMAIL PROTECTED]> wrote:
>
> I don't think running hadoop on a GPU cluster is a common use case; the
> types of workloads for a hadoop vs. gpu cluster are very different although
> a quick google search did turn up some. So this is probably not the best
> mailing list for your question.
>
> J
>
>
> On Thu, Jan 17, 2013 at 5:18 AM, Roberto Nunnari <[EMAIL PROTECTED]
> > wrote:
>
>> Roberto Nunnari wrote:
>>
>>> Hi all.
>>>
>>> I'm writing to you to ask for advice or a hint to the right direction.
>>>
>>> In our department, more and more researchers ask us (IT administrators)
>>> to assemble (or to buy) GPGPU powered workstations to do parallel computing.
>>>
>>> As I already manage a small CPU cluster (resources managed using SGE),
>>> with my boss we talked about building a new GPU cluster. The problem is
>>> that I have no experience at all with GPU clusters.
>>>
>>> Apart from the already running GPU workstations, we already have some
>>> new HW that looks promising to me as a starting point for a GPU cluster.
>>>
>>> - 1x Dell PowerEdge R720
>>> - 1x Dell PowerEdge C410x
>>> - 1x NVIDIA M2090 PCIe x16
>>> - 1x NVIDIA iPASS Cable Kit
>>> (Dell forgot to include the iPASS adapter for the R720!! :-D)
>>>
>>> I'd be grateful if you could kindly give me some advice and/or hint to
>>> the right direction.
>>>
>>> In particular I'm interested on your opinion on:
>>> 1) is the above HW suitable for a small (2 to 4/6 GPUs) GPU cluster?
>>> 2) is apache adhoop suitable (or what could we use?) as a queuing and
>>> resource management system? We would like the cluster to be usable by many
>>> users at once in a way that no user has to worry about resources, just like
>>> we do on the CPU cluster with SGE.
>>> 3) What distribution of linux would be more appropriate?
>>> 4) necessary stack of sw? (cuda, hadoop, other?)
>>>
>>> Thank you very much for your valuable insight!
>>>
>>> Best regards.
>>> Robi
>>>
>>
>> Anybody on this, please?
>> Robi
>>
>>
>