"The DAOS parallel filesystem has a strong IO500 presence, holding positions 1 (Argonne) and 2 (LRZ) in the current Production SC25 list. The two, according to HPE, combined have four times the storage benchmark score of the next 30 storage systems. DAOS also appears at number 13 (Zuse Institute, Berlin), and 17 (China Telecom Research Institute). The software appears more often in the full IO500 list, with 16 of the top 30 submissions using DAOS, and 26 of the top 45 being DAOS devotees."
"But DAOS is widespread, with 15 to 20+ production systems in active use. For its use to spread, it has to demonstrate, we understand, significantly better storage IO performance than competing software, meaning supporting more processing cores and delivering higher bandwidth. DAOS is open-source code and no single parallel processing storage system supplier is reliant on it. HPE has its ClusterStor as well as DAOS. DDN has its Lustre software, and VAST and WEKA each have their own software."
"The IO500 measures storage IO performance while the TOP500 rates pure supercomputer power. Nvidia GPU systems are appearing in it, with the number 17 position held by CHIE-4, a DGX B200 system. Nvidia-based systems also appear at positions 17, 22, 24, 29, 30, and 32. AMD GPU systems are also appearing. Enakta Labs co-founder Denis Nuja reckons that in supercomputers, "Lustre is still pretty much number one. ... I haven't seen a GPFS (Storage Scale) system in a long time.""
DAOS holds multiple top IO500 positions and powers numerous production systems, including top ranks in both full and 10-node lists. The software is open source and shows strong benchmark leadership, but broader market growth requires demonstrable advantages in storage IO for AI and GPU-centric workloads. Competing solutions such as ClusterStor, Lustre, VAST, and WEKA remain available and adopted. Rising Nvidia and AMD GPU systems in TOP500 rankings increase demand for storage that scales to more processing cores and provides higher bandwidth tailored to modern AI-focused supercomputing environments.
Read at Theregister
Unable to calculate read time
Collection
[
|
...
]