SCNet AICS-A
SCNet · Sugon ParaStor · Proprietary
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.
SCNet (SuperComputing Network) delivers high-performance computing resources tailored for AI research and development. The platform supports a diverse array of scientific workflows, encompassing domains such as materials science, biotechnology, and industrial AI.
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.
SCNet was officially launched in April 2024, initiating deployment and delivering ongoing services. Since its inception, it has focused on interconnecting computing centers serving enterprises, universities, and research institutions. Access to the platform is provided via a user-paid model.
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).
ParaStor is a commercially available, enterprise-grade parallel storage system engineered for High-Performance Computing (HPC) and AI workloads. It is generally available for acquisition by research institutions and enterprises.
System Specifications:
1. Storage Platform: ParaStor F9000 (Optimized for AI & HPC)
2. Filesystem: ParaStor Distributed Filesystem
3. Node Architecture: Each storage node is equipped with 12 NVMe SSDs, designed for extreme IOPS and low latency.
For more technical details and case studies, please refer to the official product page:
https://www.sugon.com/product/storage/product_list?cate=265
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 hereby certify that the IO500 test environment is fully reproducible.
The benchmark was compiled and orchestrated using a locally built OpenMPI (version 4.1.7a1). The test utilized 500 compute nodes, with 128 MPI processes collocated per node.
Related Commands & Utilities:
Stripe Configuration Utility:/clistorage/tools/set_subdir_layout
mount options: mount -t ParaStor -o fsname=fs01 -o sysname=scnet -o noatime,utf8 -o user_xattr -o rw -o export/ scent_fs01_ /mnt/fs01
All relevant tuning artifacts and configuration files (e.g., io500.sh, MPI hostfiles, mount options) can be shared upon request or included in the submission package.
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.
As a production system, this system has no single point of failure, in accordance with "Definition 7."
Power:
Each server is equipped with dual power supplies (1+1 redundancy), drawing power from a redundant UPS infrastructure. The architecture tolerates the failure of any single UPS unit without interruption.
Networking :
Each server features four 400Gb NIC ports, each linked to one of four distinct switches, tolerating the failure of any three components (ports or switches).
Inter storage data and metadata server:
Data is protected by EC 14+2P, and metadata by triple replication. The system is designed to tolerate up to two simultaneous node or disk failures, ensuring zero data loss and business continuity.
Intra storage data and metadata server storage media:
System disks: RAID 1 (2 drives, 1-drive fault tolerance). Data: EC 14+2. Metadata: Triple replication. The cluster sustains up to two concurrent node or disk failures, ensuring zero data loss and business continuity.
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?
Jobs were run on the compute cluster via the system scheduler (Slurm), which first executed a setup process to configure the client , and then launched the full IO500 benchmark..
Concurrent jobs were run on the same cluster(other computing nodes) and shared storage system during the IO500 benchmark execution.
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 ParaStor client is architected as a kernel-native driver, interfacing directly with the Linux VFS. It utilizes the Linux page cache for unified data and metadata I/O handling, ensuring strict POSIX compliance with minimal overhead.
Cache Hierarchy Configuration:
• Client-side Data/Metadata: It is implemented as a kernel-native module with a fully in-house designed architecture, incorporating a Distributed Lock Manager (DLM). Cached data is globally visible and maintains strict cache coherency across all compute nodes. (Active).
• Client-side NVMe Read-only Cache: Unused.
• Storage Server Data/Metadata: It is implemented as a user-space (FUSE-based) solution with a fully in-house designed architecture. Metadata reliability is ensured through journaling and multi-replica redundancy, guaranteeing strong crash consistency. Data is written directly to NVMe SSDs via Direct I/O. (Active).
• Storage Controller Cache: Unused.
• RAID Card Cache: Unused.
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 is a stand-alone primary storage system, not merely an acceleration layer or cache fronting a separate persistent storage backend.
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"?
Benchmarks were executed repeatedly under identical conditions, yielding similar scores. The submitted result represents a single run from this reproducible set.
All observed IOPS and bandwidth aligned with established hardware limits.
ParaStor adheres to standard POSIX semantics and enforces data commitment to persistent storage prior to acknowledging close operations. This behavior was verified through cross-node validation, confirming immediate file accessibility and durable writes upon benchmark completion.