Gluesys-TTA IO500 Testbed
Gluesys · Gluesys ExaStor · 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 submitted system, powered by Gluesys ExaStor, is specifically designed for high-performance computing (HPC) workloads and AI-optimized data management. It supports data-intensive applications such as deep learning training, large-scale systems research, and high-throughput benchmarking. The data generated by these applications requires massive parallel I/O capabilities and low latency, which this storage system effectively delivers.
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.
This system is built as a commercial production solution deployed within a dedicated high-performance environment. It is engineered to support AI research centers and enterprise customers requiring robust parallel and distributed storage infrastructures. The system has been active for intensive evaluation and performance benchmarking since March 2026, serving high-performance file system engineers and system architects as its primary and most regular user base.
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 runs on "Flexa," a proprietary operating system built upon Rocky Linux 8.10 that integrates OpenZFS and the community edition of the Lustre file system. While the storage core of our ExaStor commercial software is not publicly open-source, the full source code of the remaining system components is provided directly to purchasing customers. Furthermore, to ensure complete reproducibility for evaluation, we provide the standard RPM packages and full tuning scripts utilized during this IO500 benchmark run.
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.
We have provided comprehensive configuration details and custom scripts within the extraCodes upload to ensure complete environment reproducibility. This submission includes specific file system tuning parameters, layout settings for Lustre cluster volumes, and non-default configuration metrics. All custom scripts used to execute and monitor the IO500 benchmark have been shared to allow exact replica testing.
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 submitted ExaStor F824DC model utilizes an AIC HA2026-HC dual-port NVMe storage hardware platform, engineered to completely eliminate any single point of failure (SPOF). Redundancy is fully implemented across all hardware and software layers, including dual power cables, active-active controllers, redundant network interfaces, and clustered OS configurations. High availability and non-disruptive continuous operations are achieved by seamlessly combining the Lustre file system with Pacemaker clustering.
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 benchmark was executed on a bare-metal environment without the use of Kubernetes or the Slurm workload manager, ensuring that the entire storage system and compute cluster were 100% dedicated to this run. The execution sequence precisely initialized client configurations via mount2.sh and configured the Lustre file system paths using create_cluster.sh and create_test_dir.sh. Finally, the fully automated benchmark suite was driven via run.sh to capture exact, raw maximum performance metrics without virtualization overhead.
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
To maximize and accurately measure the raw performance of the underlying NVMe storage tier, the ior I/O benchmarks were configured to use direct I/O (O_DIRECT), bypassing client-side caching. For all other remaining tests within the suite, standard Linux page and memory caching mechanisms along with server-side RAM caching were utilized as part of the native parallel file system behavior.
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 submitted system operates strictly as a stand-alone, primary parallel storage system and does not function as a temporary acceleration layer or burst buffer. It acts as the absolute source of truth for all application data, maintaining persistence and handling all read/write workloads directly on its own highly integrated NVMe storage tier.
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"?
The final benchmark results are highly trustworthy and fully reproducible on the submitted system configuration. We executed the benchmark multiple times using identical tuning parameters and consistently achieved stable, tight-variance scores. Each result was thoroughly evaluated against the physical capabilities of our hardware components—including network bandwidth, NVMe SSD throughput, CPU, and memory limits—confirming that the metrics are entirely reasonable and realistic. Additionally, we verified that all data was persistently committed to storage in strict compliance with the IO500 persistence rules.