Cluster: BOSE
Brought online in 2021, BOSE is the newest and our flagship cluster at the Blugold Center for High-Performance Computing. Named after the Indian mathematician and physicist Satyendra Nath Bose, this cluster has successfully tripled our available resources and brought in all kinds of new research projects and opportunities that wasn't previously possible.
This cluster was funded by an NSF MRI grant (#1920220), along with an in-kind grant of hardware from Hewlett Packard Enterprise.
Are you looking to transition from BGSC to BOSE?
How To Connect
Off Campus?
If you are not on campus, you'll need to first connect to the UW-Eau Claire VPN before you can access our computing resources.
SSH / SFTP / SCP - Command Line
| Hostname | bose.hpc.uwec.edu |
| Port | 50022 |
| Username | Your UW-Eau Claire username - all lowercase |
| Password | Your UW-Eau Claire password |
| Password w/ Okta Hardware Token | UWEC Password,TokenNumber |
Using a hardware token or code with Okta?
By default, when you connect to our BOSE cluster over SSH, a push notification will be sent to the Okta Verify app on your phone for you to approve.
If you are unable to use your phone and are using a hardware token or six-digit code, you'll have to put the number you receive on the device directly after your password separated with a comma before you can log in.
Example:
Username: myuser
Password: mypass,123456
OnDemand Portal - Web Browser
Connecting to our computing cluster can be done right in your web browser, as long as you are connected to the UW-Eau Claire network.
Website: https://ondemand.hpc.uwec.edu
Hardware Specs
Overall Specs
| Hardware Overview | # Total |
|---|---|
| # of Nodes | 65 |
| CPU Cores | 4,160 |
| GPU Cores | 61,440 |
| Memory | 18.6 TB |
| Network Scratch | 64 TB |
Node Specs
| Node Name | CPU Model | CPU Cores (Total) | CPU Clock (Base) | Memory (Slurm) | Local Scratch |
|---|---|---|---|---|---|
| cn[01-56] dev01 |
AMD EPYC 7452 (x2) | 64 | 2.35 GHz | 245 GB | 800 GB |
| gpu[01-03] | AMD EPYC 7452 (x2) | 64 | 2.35 GHz | 245 GB | 400 GB |
| gpu04 | AMD EPYC 7452 (x2) | 64 | 2.35 GHz | 1 TB | 400 GB |
| lm01 | AMD EPYC 7452 (x2) | 64 | 2.35 GHz | 1 TB | 400 GB |
| lm[02,03] | AMD EPYC 7452 (x2) | 64 | 2.35 GHz | 1 TB | 800 GB |
Graphic Cards
We have four nodes containing three NVIDIA Tesla V100S 32 GB graphic cards under the "GPU" partition.
Slurm Partitions
| Name | # of Nodes | Max Time Limit | Purpose |
|---|---|---|---|
| week | 55 | 7 days | General use partiton. It should be used when your job will take less than a week, or if you can restart your job to continue running it from a checkpoint. This partition has the most nodes and is highly recommended for most jobs. |
| month | 8 | 30 days | Special partiton for longer-length jobs, but nodes are shared with the week partition. |
| magma | 10 | 7 days | Partition for any jobs that need to use the software Magma Computational Algebra System. |
| GPU | 4 | 7 days | Partition that uses exclusively nodes that contain GPUs, only to be used when GPUs are required for your job. Note: You must specify –gpus=# to indicate how many GPUs you want to use. |
| highmemory | 3 | 7 days | Partition for jobs that require large amounts of memory to compute. Our two nodes support up to 990GB of memory. |
| develop | 1 | 7 days | Development partition for software that needs additional libraries to be compiled. |
| pre | 55 | 2 days | Low-priority partition available on all nodes, but jobs may be requeued if resources are needed by a job on another partition. |
Acknowledgement
We request that you support our group by crediting us with the following message in your papers whenever using the BOSE supercomputing cluster for your research.
The computational resources of the study were provided by the Blugold Center for High-Performance Computing under NSF grant CNS-1920220.
