CSSP
Saudi ARAMCO · DDN Storage · 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.
Oil & Gas applications and data exploitation. Used mainly for seismic applications.
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 deployed in December 2023 and will be serving for 5 to 7 years. It is the on-premises system for ARAMCO users and is only available to users inside the organization.
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).
This system is used to exploit seismic data for oil and gas purposes using commercial and in-house built applications.
The software used for this system is the closed-source DDN software EXAScaler 6.x on top of the open-source DDN Lustre 2.14.
The system runs on 10 DDN SFA400NVX2E appliances for data and one DDN SFA200NVXE appliance for metadata. The clients and servers are connected through an 100GbE interconnect.
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.
io500.sh is used to submit io500 benchmark included in the tarball as well as uploaded seperately.
The following tuning is used for server and client.
Server
"llite.*.max_read_ahead_mb" = 2048
"obdfilter.*.brw_size" = 16
"osc.*.max_dirty_mb" = 512
"osc.*.max_pages_per_rpc" = "16M"
"osc.*.max_rpcs_in_flight" = 32
"osd-ldiskfs.*.read_cache_enable" = 0
"osd-ldiskfs.*.writethrough_cache_enable" = 0
Client
lctl set_param osc.*.max_pages_per_rpc=16M
lctl set_param osc.*.max_rpcs_in_flight=32
lctl set_param osc.*.max_dirty_mb=1024
lctl set_param llite.*.max_read_ahead_mb=4096
lctl set_param llite.*.max_read_ahead_per_file_mb=256
lctl set_param osc.*.checksums=0
lctl set_param mdc.*.max_rpcs_in_flight=128
lctl set_param mdc.*.max_mod_rpcs_in_flight=127
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.
The system is designed without a single point of failure.
Multiple power sources ensure a redundant power supply for the storage equipment.
Each server is bonded with Dual 100GbE interconnect to overcome single link failure.
All servers operate in an active-active mode.
Controller pairs mirror each other's cache, which is supported by a battery backup in the event of a power outage.
Declustered RAID employs an 8+2 configuration to safeguard data against the failure of one or two drives within the same logical group. This setup facilitates a rapid rebuild process to restore data integrity quickly after a drive 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 benchmark was executed using io500.sh. System dedicated for benchmark for the whole time running io500.
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 data and metadata are stored within the Linux page cache up to a limit set by client lctl max_dirty_mb parameter.
Server-side caching utilizes writethrough and read page caching.
Storage controllers utilize caching that is mirrored between controllers.
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.
Stand-alone storage system, there is no acceleration layer in front
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"?
Test ran multiple times, the scores lies between 53-55 on successful run.
The throughput is below peak performance of the system but metadata tests seems OK given configuration.
All benchmark was run against persistent storage.