DACH Storage Scale System 3500

IBM Ehningen System · IBM bb145nvme · 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.

The system is primarily used for performance engineering, test, and measurements/benchmarking.  A primary use of this system is the benchmark work required to respond to sales RFI/RFPs. 

Another example of performance engineering work would be debugging performance problems and testing new code intended to improve performance.

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 resources are always in use and generally in the same cluster format although the Storage Scale servers may be split into separate building blocks and the client nodes may mount other file systems for different storage servers. 
If there’s a need to do a larger config change, like split the servers into separate building blocks, the timeframe to redeploy this cluster in a different configuration can range from hours to up to a day.

The system is available for team members that work on IBM Storage Scale, with the primary users being performance engineers, often working directly with our sales team.

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).

IBM Storage Scale (the file system software) and Red Hat (the operating system) are generally commercially available.

Anyone can purchase the software or download a limited use version (it is available commercially).

The product webpage is https://www.ibm.com/products/storage-scale

Regarding the specific storage deployment, this submission uses three building blocks of the IBM Storage Scale 3500 solution, which is described here: https://www.ibm.com/downloads/cas/R0Q1DV1X

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.

All scripts and additional documentation have been included in the io500.tgz file. 
Here are the tuning and configuration steps used:

1.    The exact ‘mmchconfig’ options that were tuned are included (in the mmlsconfig file) in .tgz file included.  Details on how these file system configuration options are set are described in the included file:  README.fs_config

2.    Using the ‘mmchnode’ all nodes (clients and servers) have been defined as ‘manager’ role nodes as shown in ‘mmlscluster’ file attached

3.    The PCI tuning option PCI_WR_ORDERING has been enabled on all nodes as follows:

Find the MST device name of each adapter, e.g.:

mst start
mst status
/dev/mst/mt4129_pciconf0

Enable PC_WR_ORDERING for each such device, e.g.:

mlxconfig -d /dev/mst/mt4129_pciconf0 s PCI_WR_ORDERING=1 

<reboot for the change to take effect>

4.    As shown in the mmlsfs file attached (named mmlsfs_bb145nvme), the file system block is 4MB (file system block size is a choice based on the use case)

5.    Details on the io500 run itself are in the README.io500_config file that’s attached to the ZIP

6.    The details of the external pfind script used are in the find_script directory included in the ZIP

7.    The choice of erasure encoding used is 8+2P, which is a choice based on the use case (8+2P is the most common erasure encoding option used for the storage configuration)

8.    The file system created for the io500 run preallocates 500M inodes and uses a file system version of 5.1.7 (--mmcrfs --inode-limit 500M:500M --version=5.1.7)

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.

IBM Storage Scale servers are designed with power redundancy in mind.
The network switches are a single point of failure (we do not have dual redundant fabrics).
The storage subsystem employs IBM Storage Scale RAID to use 8+2 erasure encoding and, for some metadata, replication to protect file system data from hardware component failures.

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?

The benchmark was executed directly by calling the ‘io500.sh’ script that has been included in this submission.  Additional details on how io500.sh was run are included in the README.io500_config file that is attached to the .tgz file included.

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

On the client side, the Storage Scale pagepool (in RAM) is used to cache data in the same manner that the Linux file cache is used to cache data with other file systems such as ext4.  Data is not cached on NVMe drives on the clients as those client drives are not used in the I/O path by the Storage Scale file system.

On the server side, a portion of the servers’ Storage Scale pagepool (RAM) is also available for caching.  The effect of this caching provides similar caching to that obtained using solid state drive caching systems, and the NVMe drives on the servers also provide solid state caching.

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.

There is no burst buffer used – it is the primary storage itself.  Caching on the server-side page pool is analogous to how disk drive caching works.

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"?

Very similar scores have been achieved in several other runs of the benchmark on the same system (e.g., 166.049756, 163.581248).

We have validated that the scores achieved are within the physical capabilities of the system.