At the core of DSRS lies a powerful, flexible, and secure infrastructure designed to support advanced research. Our architecture integrates leading open-source tools, cloud platforms, and virtualized resources to enable scalable, on-demand computing environments for diverse research needs.
The DSRS infrastructure's backbone is a high-performance computing cluster consisting of 486 CPU cores across 24 nodes, 2.2 TB of RAM, 110 TB of NFS storage, and 2 NVIDIA A100 80 GB GPUs. This setup provides substantial computational power to support a multitude of research projects simultaneously.
The cluster, managed by OpenStack, provides virtual machines for individual applications, including our blockchain applications and other environments tailored to specific research groups. Within this architecture, we also deploy a Kubernetes cluster using Terraform and Rancher, giving us the flexibility to scale workloads on demand.
On top of this Kubernetes cluster, we deploy applications managed by Argo CD, a GitOps continuous-delivery platform. All manifests and configurations live in GitHub and stay in sync with the cluster, so every change is version-controlled and auditable. We also run n8n for workflow automation and host LLM/AI inference endpoints backed by our A100 GPUs.
An important part of the infrastructure is our JupyterHub environment, used both internally and by other research groups within the college. We can provision a hub for a group or deploy individual labs with a line of configuration. This environment, complemented by frameworks like Dask and Spark, supports parallel execution of machine learning models and makes interactive research readily accessible.
To support a wide variety of research activities, we run databases including MongoDB, PostgreSQL, MySQL, Neo4j, TimescaleDB, and Redis. We also provide S3-compatible object storage via MinIO and a dropbox-like file sharing service. Security is handled through OAuth2 Proxy for authentication and HashiCorp Vault for secrets management.
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