The Computational and Data Science (CDS) PhD Program at Middle Tennessee State University (MTSU) provides access to two high-performance computing (HPC) clusters: Babbage and Hamilton. These clusters are designed to support computational and research-intensive tasks for CDS faculty and students. This document provides an overview of their computational resources, configurations, and usage capabilities.
Babbage is a 21-node cluster optimized for general-purpose computation, high-memory applications, and GPU-accelerated workloads. It is optimized for general-purpose computation, high-memory applications, and GPU-accelerated workloads.
| Category | Details |
|---|---|
| Total Nodes | 21 |
| CPUs | 692 threads (various Intel architectures) |
| RAM | 2,752 GB |
| GPUs | 13 GPUs (2080Ti and A5000 models) |
| Centralized Storage | ~80 TB |
| Node Name(s) | CPU | RAM | GPU | VRAM | Special Features |
|---|---|---|---|---|---|
c1-10 |
32 threads, Intel Broadwell | 64 GB | None | None | General Purpose |
c11-14 |
32 threads, Intel Sandy Bridge EP | 64 GB | 2x NVIDIA 2080Ti | 11 GB each | GPU Nodes |
c15-16 |
72 threads, Intel Cascade Lake | 768 GB | None | None | High Memory Nodes |
c17-21 |
20 threads, Intel Cascade Lake | 64 GB | 1x NVIDIA A5000 | 24 GB | GPU Nodes (soon upgraded to 2x A5000 with NVLink for 48 GB linked VRAM) |
Scratch Space: Each node has 1 TB of local scratch space for temporary job storage.
Hamilton is a 9-node cluster tailored for research tasks requiring GPUs and specialized computational resources. It is tailored for research tasks requiring GPUs and specialized computational resources.
| Category | Details |
|---|---|
| Total Nodes | 9 |
| CPUs | 180 threads (Intel and AMD architectures) |
| RAM | 640 GB |
| GPUs | 9 GPUs (2080Ti and A100 models) |
| Centralized Storage | ~40 TB |
| Node Name(s) | CPU | RAM | GPU | VRAM | Special Features |
|---|---|---|---|---|---|
c1-8 |
20 threads, Intel Cascade Lake | 64 GB | 1x NVIDIA 2080Ti | 11 GB | General Purpose |
c9 |
20 threads, AMD EPYC | 128 GB | 1x NVIDIA A100 | 80 GB | High-Performance GPU |
Scratch Space: Each node has 1 TB of local NVMe SSD scratch space for temporary job storage.
Both clusters operate on Rocky Linux 8 with OpenHPC 2.0.
- SLURM is the job scheduler for both clusters. It handles resource allocation and job execution.
- High-speed 10G fiber interconnects ensure efficient data transfer between nodes.
Modules include popular software for scientific computing, such as:
- Python
- R
- Conda
- TensorFlow/PyTorch (GPU-optimized)
- MPI libraries
Both clusters are equipped with Open OnDemand for web-based access:
- Babbage: babbage-od.cs.mtsu.edu
- Hamilton: hamilton-od.cs.mtsu.edu
- Interactive Desktops: Access a full Linux desktop environment in your browser.
- Jupyter Notebooks: Create and manage Jupyter sessions with customizable resources (e.g., CPU/GPU, memory).
- File Browser: Manage files and data stored on the cluster.
- Job Management: Submit, monitor, and cancel SLURM jobs.
| Directory | Purpose | Storage Type | Notes |
|---|---|---|---|
/home |
User home directories | Centralized NFS | Limited quota; persistent |
/projects |
Shared project directories | Centralized NFS | Long-term storage |
/scratch |
Temporary storage for jobs | Local to nodes | Purged periodically |
| Partition Name | Nodes | Max Time | Special Features |
|---|---|---|---|
interactive-cpu |
c1-10 |
2 hours | Short interactive jobs |
research-cpu |
c1-10 |
72 hours | General purpose |
research-dual-gpu |
c11-14 |
48 hours | Dual GPU nodes |
research-gpu |
c11-14, c17-21 |
96 hours | Mixed GPU nodes |
research-bigmem |
c15-16 |
168 hours | High memory nodes |
| Partition Name | Nodes | Max Time | Special Features |
|---|---|---|---|
interactive |
c1-8 |
2 hours | Short interactive jobs |
research |
c1-8 |
48 hours | General purpose |
a100 |
c9 |
150 hours | High-performance A100 GPU |
For assistance with HPC resources:
- Email: tgoff@mtsu.edu
- Documentation: Additional documentation is available at help.mtsu.edu/kb under the Computational Science Systems KB.