Hello.

A contingent of my organization, the Kno.e.sis Center @ Wright State University, 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.

Thanks,
Joshua