Emmy

Gesellschaft fur wissenschaftliche Datenverarbeitung · Clyso NVMe · Fully Reproducible

System Purpose

Question asked

Please describe the purpose and general usage of the submitted system.  This would include the types of typical applications it supports (e.g., defense applications, molecular dynamics, benchmarking, system test, systems research), and the general use and purpose of the data generated by the applications running on it.

This storage system will support the Emmy and Grete Supercomputers at the University of Göttingen and the Max-Planck-Society and fuel the national AI servicecenter KISSKI.  These supercomputers support research including physics, materials science, chemistry, bioinformatics, earth system research, and engineering sciences.

Availability

Question asked

Please provide the deployment timeframe of the submitted system, or for on-demand cloud systems, the general period over which it is deployed and destroyed.

Please describe the availability of the system to users and who are its set of most regular users.

These systems currently completed testing after several months of burn in and performance tuning and will now be deployed into production for end users.

Storage System Software

Question asked

How is this storage software available? (e.g., commercially, open-source, not publicly available) Note that if the storage software is not open-source or commercially available, then a general description would be requested, but this would limit the submission’s reproducibility score.

Can anyone download/purchase this software?

List either product webpage or open-source repo of the exact software used in IO500.

Give any and all additional details of this specific storage deployment: (e.g., type of storage server product such IBM ESS or DDN SFA400X2, use of Ext4 or some other file system on each storage node, dual connected storage media to storage servers).

Usage information is provided in the earlier answer.  Ceph itself is open source and we are proud of our open source heritage.  Anyone can download the software.  In this case, we are using Ceph running on top of Garden Linux which is also open source.

https://www.ceph.io/en/

https://github.com/gardenlinux/gardenlinux

This cluster is deployed on eight Dell nodes with twenty NVMe drives each.  Each node is connected via 100GbE.   Ceph itself stores data directly on block devices using the "bluefs" compatibility shim to provide virtual filesystem access for RocksDB where we store object metadata.

Runtime Environment

Question asked

State here that you provided all scripts/documentation that would allow someone else to reproduce your environment and attempt to achieve a similar IO500 score as the submitted system.

NOTE: provide all files/documentation/scripts that would enable a user to build your environment and deploy the custom scripts, software, or config files once they have obtained the appropriate storage system hardware and software. These may be included into the io500.tgz or into the extraCodes upload on the submission form.

Several examples include:

  • Commands used to set striping information (either for the entire system or for particular directories)
  • File system config and tuning information (or a reason why this is not available due to lack of root access, etc) on each node type (e.g., non-default config parameters on all three types of Lustre nodes: MDS, OSS, and client)
  • Any additional scripts utilized that impact IO500 execution beyond the io500 config file. For example, with IBM Spectrum Scale, the output of mmlsconfig, mmlscluster, mmlsfs, and mmlsfileset commands (and possibly even a dump of the configuration if possible). Each file system probably has similar type of config/tuning information that would need to be shared for a user to fully reproduce the environment.

In addition to the pinning strategy documented in the io500.sh script (included in the results archive), several additional tuning steps were performed to improve Ceph performance.  Primarily these were:

  • Inceasing the per-mds cache limit to 64GB
  • Setting OSD memory targets to a reasonable ratio of the remaining memory on the nodes.
  • Increasing the number of active MDSes to 28
  • Ensuring that CPU c-state transitions are not allowed (always run in high power states)
  • Making sure CPU hyperthreading is enabled
  • Disabling client-side page cache

Fault Tolerance Mechanisms

Question asked

Does your system have a single point of failure as defined by “Definition 7” of a Production System? Please describe all mechanisms that provide fault tolerance for the submitted storage system. Be specific to your submission, not general storage system capabilities.

  • Power (For example, can power failure of a node or rack bring down the storage system?)
  • Networking (For example, can failure of a single NIC bring down the storage system? Remember that any networking failure that brings down multiple nodes is acceptable)
  • Inter storage data and metadata server (For example, what type of data protection mechanism does the storage system use to keep operating during node failures, e.g., active-active servers, client-directed RAID, declustered RAID, erasure-coding, 3-way replication)
  • Intra storage data and metadata server storage media (For example, how does the storage eysstem protect against fiailure of a single storage device within a node, e.g., raid5)

Please list any additional information needed to determine whether this system has a single point of failure.

Ceph is extremely fault tolerant and allows storage to be distributed across different arbitrary failure domains such that the loss of a disk, node or even a rack does not cause a storage outage when configured as such.

Execution

Question asked

Please provide a description of how the IO500 benchmark was executed, e.g., via system scheduler (e.g., SLURM) to run a job on the compute cluster, which initially ran a setup process to configure the client and file system, and then started the full benchmark.

During the IO500 benchmark execution was the system entirely dedicated to running the benchmark or were there other jobs running in the same cluster and storage system?

A short preparation script was used to download and compile MPI and the IO500 benchmark.  The io500 script and configuration files were copied from a central repository to the final run location.  Finally, the benchmark was then run manually by hand.  In this case both the storage system and utilized client nodes were 100% dedicated to running the benchmark.

Caching

Question asked

Please describe all caching mechanisms in client/server that were utilized during the IO500 run. This could include caching in any storage medium (e.g., SSD, RAM).

A few examples would include:

  • Client data/metadata caching (in Linux page cache or in other memory cache)
  • Client side NVMe read-only data cache
  • Storage server metadata/data caching in RAM
  • Storage controller caching
  • RAID card caching
  • Client page cache was disabled to improve the performance of ior-hard-read.
  • Certain filesystem related metadata and caps were stored in per-MDS caches.
  • Object  related metadata and potentially buffer data was cached in OSD caches governed by the global Ceph OSD memory target.
  • per-NVMe volatile write cache was utilized in conjuction with power loss protection to allow fast fsync/fdatasync during object writes.

Data Source

Question asked

Is the submitted system a stand-alone storage system or an acceleration layer in front of another storage system that is the source of truth for all application data? This question relates to whether the submitted system is a burst buffer layered on primary storage or primary storage itself.

This is a stand-alone storage system.  There are no burst-buffers involved.

Trust

Question asked

Please describe any steps taken to ensure that the results are trustworthy.

  • Did you run the benchmark multiple times and get similar scores?
  • Did you validate the score is below the physical capabilities of the deployed hardware?
  • How did you validate that the storage system follows the IO500 rules regarding persistence, which states, "All data must be written to persistent storage within the measured time for the individual benchmark, e.g. if a file system caches data, it must ensure that data is persistently stored before acknowledging the close"?

Did you run the benchmark multiple times and get similar scores?

We went through a 13 phase process of repeated testing, tweaking different parameters until we stabalized at the score we achieved.  Due to the samewhat chaotic nature of Ceph's dynamic subtree partitioning scheme, there can be some variability between runs in some of the tests.

Did you validate the score is below the physical capabilities of the deployed hardware?

Yes

How did you validate that the storage system follows the IO500 rules regarding persistence, which states, "All data must be written to persistent storage within the measured time for the individual benchmark, e.g. if a file system caches data, it must ensure that data is persistently stored before acknowledging the close"?

Ceph goes out of it's way to guarantee the persistence of writes to the underlying storage media.  We use a combination of write-ahead logging and issuing sync commands to the disk to ensure the orderly persistence of data.  We also have multiple layers of crc32c checks as first class citizens in our data pipeline.