Imperial - hx cluster

Imperial College London · Lenovo DSS-G · 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 is a general purpose high performance computing system support researchers from across the breadth of research conducted at Imperial College London. The system will be used with many different applications from molecular dynamics, computational fluid dynamics, ab initio quantum mechanical calculations to image processing and machine learning.

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.

The system is available to any researcher at Imperial College who require access to computational resources supporting either parallel processing across multiple compute nodes, or GPGPU accelerated applications.

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).

The system will be used with many different applications from molecular dynamics, computational fluid dynamics, ab initio quantum mechanical calculations to image processing and machine learning.

This is a commercial software from IBM that was developed as a storage applicance by Lenovo

DSS-G - Distributed storage solution based on GPFS

Spectrum Scale Erasure Code Edition ECE provides all the features of the Data Management Edition plus support for storage rich servers with network-dispersed erasure coding, distributing data and metadata across the internal disks of a cluster of servers

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.

Storage Subsystem 1 - 1 number of DSS-G240 -- 2 x ThinkSystem SR650 servers
Storage Subsystem 2 - 14  number of DSS-G100 -- 14 ThinkSystem SR630 server

140 -  3.2TB Mixed Use NVMe PCIe 4.0 x4 HS SSD


File System Type: IBM Spectrum Scale 

Spectrum Scale Erasure Code Edition brings the IBM Spectrum Scale RAID functionality to the next level, supporting the creation of scale-out network-dispersed Spectrum Scale clusters on storage rich servers. You get the same benefits of IBM Spectrum Scale and IBM Spectrum Scale RAID without the need for storage enclosures:

  • Reed-Solomon highly fault tolerant declustered RAID, protecting against drive and node failures.
  • Disk Hospital to identify abnormal behavior and mitigate issues preventively.
  • End-to-end checksum to identify and correct errors from the client over the network down to the block on the device.

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.

  • HDR infiniband interconnect with 400 Gbps per ECE node
  • DSS-G100 is a server with internal disks; ECE is a scale-out solution providing software redundancy (network RAID)

  • Declustered RAID, erasure-coding, 3-way replication
  • Small increments (1 node); NVMe support
  • Servers (each serves  two log groups)
  • Single-ported drives in servers (software redundancy)
  • Runs on commodity storage-rich servers
  • Leverage cost advantages of high volume server platforms
  • Survive concurrent loss of nodes and disks

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?

It was executed command line

time mpirun -np 256 -ppn 8  -hostfile ./hostfile -v6 -genv I_MPI_FABRICS shm:ofi -genvall /gpfs/home/spalani1/io500/io500 config-all.ini

Hostfile contains the list of comput enodes

The complete storage is dedicated as well as the compute are for the benchmark purpose 

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

The data and meta data storage in the same underline storage 

GPFS Page pool is used on the controller nodes 

Every client is dedicated with 4G page pool for read ahead and write behind

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.

GPFS pagepool is on the promary storage itself for read write operation

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"?

There are multiple runs have been performed

  • Combination of MPI procs
  • Nodes from different switches
  • Nodes from multiple racks

Every single runs gives deviation in the results, Best was chosen

The data is persistently stored on the system