Anvil CPU
Purdue's Anvil cluster built in partnership with Dell and AMD consists of 1,000 nodes with two 64-core AMD EPYC "Milan" processors each and delivers over 1 billion CPU core hours each year, with a peak performance of 5.1 petaflops. Each of these nodes has 256GB of DDR4-3200 memory. A separate set of 32 large memory nodes has 1TB of DDR4-3200 memory each. Anvil's nodes are interconnected with 100 Gbps Mellanox HDR100 InfiniBand.
Anvil CPU resources provide general-purpose computing nodes for a wide range of research workloads. They are suitable for data processing, simulations, and other tasks that do not require GPUs.
- Users can use their ACCESS account to receive an allocation and login.
- Logging into your ACCESS account will require Duo two-factor authentication.
Files in scratch directories are not recoverable. Files in scratch directories are not backed up. If you accidentally delete a file, a disk crashes, or old files are purged, they cannot be restored.
$PROJECTspace. The project space will be created for each allocation. $PROJECT and $WORK variables refer to the same location and can be used interchangeably.
ANVIL CEPH
Anvil Ceph is intended to provide scalable, fault-tolerant, and high-throughput storage for large or persistent research data. It supports both object and block storage, making it suitable for hosting shared datasets, storing long-term research outputs, and enabling data access for containerized or cloud-integrated workflows. Ceph complements the Lustre-based storage tiers by offering durable and easily expandable storage for diverse data management needs.
Inspecting file system quotas
To check the quota of different file systems, type myquota at the command line.
Notes:
- Specify your desired partition to prevent it from being automatically assigned to the shared queue
- e.g.:
-p wholenode
- e.g.:
- For node-exclusive (wholenode and wide) queues, your job will automatically be allocated one full node.
See Anvil example job scripts - https://www.rcac.purdue.edu/knowledge/anvil/run/examples
https://datasetdocs.readthedocs.io/en/latest/ai/index.html
https://datasetdocs.readthedocs.io/en/latest/Covariates/index.html
https://datasetdocs.readthedocs.io/en/latest/geospatial/index.html
https://datasetdocs.readthedocs.io/en/latest/hydrological/index.html
https://datasetdocs.readthedocs.io/en/latest/igenomes/index.html
https://datasetdocs.readthedocs.io/en/latest/meteorological/index.html
https://datasetdocs.readthedocs.io/en/latest/geoai/index.html