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    OpenStack File Services for HPC Q&A

    We got some great questions during our Webcast on how OpenStack can consume and control file services appropriate for High Performance Computing (HPC) in a cloud and multi-tenanted environment. Here are answers to all of them. If you missed the Webcast, it’s now available on-demand. I encourage you to check it out and please feel free to leave any additional questions at this blog.

    Q. Presumably we can use other than ZFS for the underlying filesystems in Lustre?

    A. Yes, there a plenty of other filesystems that can be used other than ZFS. ZFS was given as an example of a scale up and modern filesystem that has recently been integrated, but essentially you can use most filesystem types with some having more advantages than others. What you are looking for is a filesystem that addresses the weaknesses of Lustre in terms of self-healing and scale up. So any filesystem that allows you to easily grow capacity whilst also being capable of protecting itself would be a reasonable choice. Remember, Lustre doesn’t do anything to protect the data itself. It simply places objects in a distributed fashion of the Object Storage Targets.

    Q. Are there any other HPC filesystems besides Lustre?

    A. Yes there are and depending on your exact requirements Lustre might not be appropriate. Gluster is an alternative that some have found slightly easier to manage and provides some additional functionality. IBM has GPFS which has been implemented as an HPC filesystem and other vendors have their scale-out filesystems too. An HPC filesystem is simply a scale-out filesystem capable of very good throughput with low latency. So under that definition a flash array could be considered a High Performance storage platform, or a scale out NAS appliance with some fast disks. It’s important to understand you’re workloads characteristics and demands before making the choice as each system has pro’s and con’s.

    Q. Does “embarrassingly parallel” require bandwidth or latency from the storage system?

    A. Depending on the workload characteristics it could require both. Bandwidth is usually the first demand though as data is shipped to the nodes for processing. Obviously the lower the latency the fast though jobs can start and run, but its not critical as there is limited communication between nodes that normally drives the low latency demand.

    Q. Would you suggest to use Object Storage for NFV, i.e Telco applications?

    A. I would for some applications. The problem with NFV is it actually captures a surprising breadth of applications so of which have very limited data storage needs. For example there is little need for storage in a packet switching environment beyond the OS and binaries needed to stand up the VM’s. In this case, object is a very good fit as it can be easily, geographically distributed ensuring the same networking function is delivered in the same manner. Other applications that require access to filtered data (so maybe billing based applications or content distribution) would also be good candidates.

    Q. I missed something in the middle; please clarify, your suggestion is to use ZFS (on Linux) for the local file system on OSTs?

    A. Yes, this was one example and where some work has recently been done in the Lustre community. This affords the OSS’s the capability of scaling the capacity upwards as well as offering the RAID-like protection and self-healing that comes with ZFS. Other filesystems can offer those some things so I am not suggesting it is the only choice.

    Q. Why would someone want/need scale-up, when they can scale-out?

    A. This can often come down to funding. A lot of HPC environments exist in academic institutions that rely on grant funding and sponsorship to expand their infrastructure. Sometimes it simply isn’t feasible to buy extra servers in order to add capacity, particularly if there is already performance headroom. It might also be the case that rack space, power and cooling could be factors in which case adding drives to cope with bigger workloads might be the only option. You do need to consider if the additional capacity would also provoke the need for better performance so we can’t just assume that adding disk is enough, but it’s certainly a good option and a requirement I have seen a number of times.

     

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