Grant Proposal: Difference between revisions

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*** Cores: 64  
*** Cores: 64  
*** Ram: 512GB
*** Ram: 512GB
** Network: 10GB low latency SFP+ back-end network interconnecting each node
** Network: 10Gbit low latency SFP+ interconnect
** Storage: 91 terabytes of dedicated disk storage.
** Storage: 91 terabytes of dedicated disk storage.


Line 27: Line 27:
*** Cores: At least 40
*** Cores: At least 40
*** Ram: At least 192GB
*** Ram: At least 192GB
** GPUs: Multiple Nvidia P40, T4, A2
** GPUs: Multiple NVidia P40, T4, A2 GPUs
** Network: 10Gbit interconnect
** Network: 10Gbit interconnect
** Storage: Dedicated CEPH shared file system
** Storage: 174 TB of dedicated CEPH storage


== Systems Cluster ==
== Systems Cluster ==
Line 37: Line 37:
*** Cores: 48 (Intel)
*** Cores: 48 (Intel)
*** RAM: 256GB
*** RAM: 256GB
** Network: 10GB interconnected Nodes and Storage
** Network: 10Gbit interconnect
** Storage: 73TB
** Storage: 73TB
== Kubernetes Clusters ==
== Kubernetes Clusters ==
=== Discovery ===
=== Discovery ===
Line 60: Line 61:
*** Cores: 64 (Intel)
*** Cores: 64 (Intel)
*** RAM: 7686GB
*** RAM: 7686GB
** Network: 10GB interconnected to Storage
** Network: 10Gbit interconnected to Storage
** Storage: 30TB
** Storage: 30TB



Latest revision as of 15:30, 24 January 2024

Introduction

This page has been created as a quick reference which gathers all the available resources in a single location for the purposes of writing Grant Proposals. If you see an outdated resource or a missing resource please contact techstaff@cs.vt.edu.

Resources Available in the Department

RLogin

  • Hardware:
    • Nodes: 32 Compute 5 GPU
      • Cores: 32 Intel
      • RAM: 384GB
      • Storage: 1TB
    • Network: 10Gbit interconnect

CSRVM

To facilitate wide ranging research activities, some of the major services provided by the department include a Computer Science Research Virtual Machine cluster (CSRVM) which has the flexibility to create multi-core large scale VM's in a matter of minutes.

  • Hardware:
    • Nodes: 9
      • Cores: 64
      • Ram: 512GB
    • Network: 10Gbit low latency SFP+ interconnect
    • Storage: 91 terabytes of dedicated disk storage.

CSRGPU

This GPU Virtual Machine cluster is dedicated to GPU computation research. This is an excellent resource for prototyping small scale models in a virtual GPU environment before scaling up to larger hardware.

  • Hardware:
    • Nodes: 15
      • Cores: At least 40
      • Ram: At least 192GB
    • GPUs: Multiple NVidia P40, T4, A2 GPUs
    • Network: 10Gbit interconnect
    • Storage: 174 TB of dedicated CEPH storage

Systems Cluster

In addition, Computer Science has a ten (10) node homogeneous cluster, dedicated to systems research.

  • Hardware:
    • Nodes: 10 (Homogeneous)
      • Cores: 48 (Intel)
      • RAM: 256GB
    • Network: 10Gbit interconnect
    • Storage: 73TB

Kubernetes Clusters

Discovery

  • Hardware:
    • Nodes: 24 (Compute)
      • Cores: 1100
      • RAM: 3.2TB
    • Storage: 34TB

Endeavour

  • Hardware:
    • Nodes: 12 (Compute)
      • Cores: 728
      • GPU's: 12
      • RAM: 5.2TB
    • Storage: 42TB

CBB: Mnemosyne

High memory computation system, dedicated to computational bioinformatics research.

  • Hardware:
    • Nodes: 1
      • Cores: 64 (Intel)
      • RAM: 7686GB
    • Network: 10Gbit interconnected to Storage
    • Storage: 30TB

Secure Server Room & Graduate Area

The Computer Science department has a secure, modern, climate-controlled server room. The room is equipped with numerous sensors, controls, and backup systems to ensure all servers are continuously operating at peak performance. In addition, there is a separate secure, climate-controlled workspace for graduate students to work directly with servers and equipment, if appropriate.

Resources Available from the University

Advanced Research Computing - ARC