CHIE-4

SoftBank Corp · DDN CHIE-4 · 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.

A cloud infrastructure service for training, fine-tuning, and inference of generative AI models. Japanese LLM and generative AI models specialized for each industry in Japan will be output.

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.

System deployment period: Scheduled for 2025/07 to 2030/06. It can be used by applying through the prescribed procedures as a softbank AI cloud service for Japan. Frequent users are Softbank internal 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).

A cloud infrastructure service for training, fine-tuning, and inference of generative AI models. Japanese LLM and generative AI models specialized for each industry in Japan will be output.
Storage software is commercially available and anyone can purchase it.
DDN AI400X2
https://www.ddn.com/wp-content/uploads/2024/09/ddn-a3i-data-sheet-2024-rebrand-v4-1.pdf
https://ddn.co.jp/products/ai_storage.html

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.

Here are all the parameters configured for the benchmark.
Lustre MDS
echo 128 > /sys/module/mdt/parameters/max_mod_rpcs_per_client
for dev in /sys/block/*/integrity/write_generate; do echo 0 > $dev; done
for dev in /sys/block/*/integrity/read_verify; do echo $v > $dev; done

Lustre OSS
lctl set_param obdfilter.*.brw_size=16
for dev in /sys/block/*/integrity/write_generate; do echo 0 > $dev; done
for dev in /sys/block/*/integrity/read_verify; do echo $v > $dev; done

Lustre Client
lctl set_param osc.*.max_dirty_mb=2000
lctl set_param osc.*.checksums=0
lctl set_param osc.*.short_io_bytes=65536
lctl set_param osc.*.max_pages_per_rpc=16M
lctl set_param ldlm.namespaces.*.lru_size=0
lctl set_param ldlm.namespaces.*.lru_max_age=1000
lctl set_param mdc.*.max_rpcs_in_flight=128
lctl set_param llite.*.max_cached_mb=65536
lctl set_param llite.*.inode_cache=0

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.

Each Lustre server has two active-active network links, providing redundancy.
The Lustre servers are configured in an active-active high availability (HA) setup, and a failover is performed in the event of a failure.
Additionally, the RAID6 LUNs used in the Lustre OST/MDT are configured with DeClustered RAID, and the storage controllers are redundantly configured. The Write Back Cache (WBC) on each controller is protected by a Battery Backup Unit (BBU).
There are no single points of failure.

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 IO500 was manually run with mpirun and a hostfile.
During the IO500 running, the system was fully dedicated to benchmarking.

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 RAM of both the Lustre servers and clients is used as a Linux page cache.
The storage controllers have a Write Back Cache (WBC), which is mirrored between controllers and protected by a Battery Backup Unit (BBU).
it was no any other caching and all data and metadata was written to persistent disk storages. (NVMe)

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.

The storage in this environment is a standalone system and is used by NVIDIA superpod.

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"?

We ran the benchmark multiple times and achieved similar results.
The measured scores are reasonable and all numbers are definitely below the theoretical hardware performance.
Lustre does not keep metadata and data in memory. Everything is consistently flushed to persistent disk storage at all times.