Open Stack

At CERN, we have similar interests and aims as you describe. We're running LSF on top of the cloud to allow legacy batch
applications to use cloud resources as well as those who are talking directly to the cloud APIs.

 

To track resources, we are setting up a dedicated batch project in OpenStack. These resources are accounted to the IT department. We
then use the batch system accounting records to work out who has used what resources inside the 'virtual batch' system. We've also
been experimenting with submitting batch accounting records into ceilometer in order to consolidate the reporting into a single
technology.

 

Where we are trying to find a good solution is regarding how to use spot market resources in our cloud. If we allocate out a quota
to a project but they do not use the full resources, we want to be able to offer that quota to others on a low SLA (killed with
little warning). This allows us to get our resource utilisation up  while ensuring that projects can get the resources they're
entitled to when there is a need.

 

This is an interesting area to be getting a few sites together to share solutions.

 

Tim

 

From: Di Pe [mailto:dipeit at gmail.com] 
Sent: 26 July 2013 08:48
To: openstack-hpc at lists.openstack.org
Subject: Re: [openstack-hpc] Looking for practical Openstack + Ceph guidance for shared HPC

 

All,

 

one issue Joshua touched on was options for workload management. While IB and GPU seem to frequently discussed when it comes to
openstack and HPC they are not so relevant in our HPC environment (3000 ish cores, each node connected via 1G, scaleout NAS storage,
biomedical research, genomics, proteomics, statistics) ..... many other midsize shops may be have similar setups. We are just
starting to look at openstack for a for a potential deployment with Ubuntu 14.04. We have good experiences using KVM for some of our
resources. Some of the things we are hoping to get from openstack in the future are:

 

*	flexible partitioning of resources for special sauce software (hadoop, interactive HPC software)
*	self service for developers and scientists
*	allow research group that spans multiple research organizations (internal / external) controlled access to an isolated
(virtual) datacenter (potentially with fisma compliance)
*	save images that researchers built for later use (reproducible in case someone asks how they got to this result)
*	chargeback for HPC resources for internal and external users
*	usage of idle resources for testing in Enterprise IT, VDI ,etc
*	compute fencing (as we are heading to 24 cores per box most of our multi threaded code can still only take advantage of 4-6
cores. This either leaves stuff idle or users step on each other on shared nodes ....cgroups is a bit of a pain to maintain.
*	checkpointing and restarting long running jobs (for prioritization and better protection against job failures). perhaps LXC
containers as alternative to KVM (we use BLCR today but that community is quite small)
*	standardization of our infrastructure
*	potential participation in futuregrid, XSEDE, etc

 

That's perhaps a lot to ask but we would be looking at a 2-3 year time frame. What I don't quite unterstand, how would one handle
workload management. Currently we see people using SGE, moab, LSF and some slurm in classic HPC. Concepts like backfill, preemption
fair share and such things are probably unknown to openstack? If so it would perhaps be acceptable to run a workload manager on a
subset of always-on KVM systems or even baremetal for classic HPC. But how does one consolidate the reporting, billing, chargeback
of 2 separate systems? 

 

Are there any efforts to integrate workload managers directly into nova? SGE and Slurm are both open source and would support
everything we require. Or are folks thinking about writing something from scratch in python?

 

Thanks

dipe

 

 

 

 

On Thu, Jul 25, 2013 at 6:22 PM, Narayan Desai <narayan.desai at gmail.com <mailto:narayan.desai at gmail.com> > wrote:

Brian's right. You will end up doing a lot of work; nova isn't ready for this out of the box. 

 

The key problems are:

 - drivers for virtualization (either via SR-IOV or device passthrough) for net + gpu

 - IO architecture

 

There is apparently SR-IOV support for IB, provided that you have the right hardware, firmware, and driver, though I haven't managed
to make it work. This provides a pkey isolated multi-tenant environment. THat is basically a mellanox only solution. 

 

Like Brian said, Xen is the only way to go for GPU virtualization. 

 

You can do some really interesting things with the I/O architecture. We've been experimenting with both glusterfs and ceph. Both
seem to perform decently well; we've managed to get the glusterfs setup going at 60 GB/s in aggregate with a pile of clients. There
isn't good integration of all of the capabilities yet in mainline openstack, but this looks promising. Ceph looks like the mainline
integration is better, but we haven't tried those things out yet.

 

At the end of the day, you need to ask yourself why you want to accomplish this. If you're running a workload that is well suited to
an HPC cluster, you should probably use one. If you need multi-tenancy, user control of system software, or need to run a workload
poorly suited for a traditional cluster, then it is worth thinking strongly about. You'll end up needing to do a bunch of work
though.

 

In our case, the reason that we pursued this course is because we have workloads and developers that benefit from the cloud control
plane.

 

hth.

 -nld

 

 

On Thu, Jul 25, 2013 at 3:30 PM, Brian Schott <brian.schott at nimbisservices.com <mailto:brian.schott at nimbisservices.com> > wrote:

Joshua,

 

It is something those of us working the gap between HPC and cloud have struggled with.  We lack a strong project team within
OpenStack IMHO, although there are several small groups doing HPC with OpenStack.  Hopefully others will chime in on some other
topics, such as Infiniband support, but we did some testing with a GRID K2 card for GPU pass-through with different hypervisors.  A
talk I gave at the OpenStack DC meetup is here:

http://www.slideshare.net/bfschott/nimbis-schott-openstackgpustatus20130618

 

The short GPU answer is that it is possible with Xen, XenCenter, and XCP to passthrough GPUs today, but OpenStack doesn't have
support by default in Nova.  This is still in a roll-your-own mode for deployment.

 

Brian

 

-------------------------------------------------

Brian Schott, CTO

Nimbis Services, Inc.

brian.schott at nimbisservices.com <mailto:brian.schott at nimbisservices.com> 

ph: 443-274-6064 <tel:443-274-6064>   fx: 443-274-6060 <tel:443-274-6060> 

 

 

 

On Jul 25, 2013, at 4:06 PM, Joshua Dotson <josh at knoesis.org <mailto:josh at knoesis.org> > wrote:

 

Hello.

A contingent of my organization, the Kno.e.sis Center @ Wright State University <http://www.knoesis.org/> , recently received a
grant award which we intend to use to support a handful of mid-size HPC-style workloads (MPI <-- definitely, GPGPU <-- if
possible/plausible) in addition to many mid-size IaaS-style workloads (MongoDB, Storm, Hadoop, many others).  As a third layer, I'm
playing with the idea of evaluating an elastic OpenShift Origin atop the same infrastructure.  Approximately $400k to $500k will
hopefully be available for this deployment, though exact numbers are not yet available to me.  

While I'm prepared to build a home-grown small-to-mid-size "classical" HPC, using modern hardware, and a smaller silo for home-grown
Openstack for the minority stakeholders, I am hoping to find ways of making proponents of both workloads simultaneously happy, or
close to it.  That is, I would like to give my computer scientist users a friendly method of running their HPC-style jobs on a
combined performance-tuned silo of Openstack.  Doing so would load-balance the procured hardware and infrastructure with the users
who want a Tomcat or a Virtuoso instance.

I see a number of serious issues realizing such a goal.  For example, the state of Infiniband vs. Openstack seems not quite
ready/available/documented/accessible for such use in production, unless I'm just blind to the right blogs.  The added myriad
abstractions and latency virtualization might impose on an HPC task, not to mention cloud software defined networking (Quantum,
especially when sans hardware acceleration), seem likely to really get in the way of practicality, economics and efficiency.  That
said, most of what we do here isn't HPC, so I believe such trade-offs can be agreed upon, if a reasonable job scheduling and
workload management mechanism can be found and agreed upon by all stake holders, grant proposal majority (HPC) and minority (IaaS)
alike.  

I get the impression from my readings that HPC-style deployment (separate from job queuing) against the EC2 API should work.  I
don't have a good feeling that the experience would be particularly friendly, however, without paying for closed source
applications.  I'm thinking a high-performance Ceph install would help bring up the storage end of things in a modern open-source
CoTS way.  I've not done specific research on Lustre + Openstack, but no reports of such a setup have presented themselves to me,
either.

These blue sky ideas matter nil, it seems, if a sufficiently-large high-performance production-quality Openstack deployment is
beyond the funds to be allotted, which is something else I'm working on.  I've built smallish but useful virt-manager, oVirt and
Openstack environments here already, but none of them are enough for the very-important HPC job proposed for this grant.  The
scientist running the proposed computation gave me following information to clarify what would parity (for his job only) his
experience running the computation with an external HPC service provider.

*	MPI
*	20 Gbps Infiniband compute interconnect
*	600 cores (those currently used are probably G4 Opteron 2.4 Ghz)
*	4 GB RAM per core
*	at lest 2 TB shared storage, though I'm thinking we need much more for use by our general community
*	unsure of the storage networking topology

We're in the shopping phase for this grant award and are still playing with ideas.  It seems likely to snap back into an old-school
HPC, at this time.  I've fielded communication about our needs to a number of Openstack and hardware providers, on the hope that
they can bring something helpful to the table.

Please let know if you can point me in the right direction(s). I'm up to reading whatever text is thrown at me on this topic.  :-)

Thanks,
Joshua

-- 
Joshua M. Dotson
Systems Administrator
Kno.e.sis Center
Wright State University - Dayton, OH

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