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Wahab Cluster

wahab.hpc.odu.edu

Funded through a grant from the National Science Foundation's Major Research Instrumentation Program, the Wahab cluster offers substantial computational power to critical research projects in disciplines including cybersecurity, resilience and data-intensive science and engineering. The system's speed and power make it possible to compute and analyze enormous amounts of data related to sea-level rise, natural disasters, brain imaging, cyberattack paths, and so much more.

The Wahab Research Environment is configured with 6320 computational cores and 72 NVidia V100 GPUs, with 158 compute nodes and 18 GPU nodes. Each compute node contains 40 cores at 2.4Gh and 368Gb RAM. All nodes are connected via a Mellanox Infiniband EDR backbone providing 100Gbps throughput. The GPU nodes each contain four NVidia V100 GPUs, and each V100 contains 640 tensor cores to facilitate deep learning research.

The cluster is open to all campus researchers and will serve the research computing needs of the students and faculty at ¹ÏÉñÍø for years to come.

The Wahab cluster is supported in part by National Science Foundation's grant CNS-1828593, ".

CCI-R Environment

COVA CCI is southeastern Virginia's engine for research, innovation, and commercialization of next-generation cybersecurity technologies particularly in the areas of Cyber Physical Systems Security (CPSS), 5G, and Artificial Intelligence (AI) in the Maritime, Defense, and Transportation industries.

CCI Research Overview

The COVA CCI research environment is focused on advancing research in the coastal Virginia region. It consists of a private cloud with the ability to host research applications customized to specific research needs.

The advantages of using the research cloud over your typical workstation include:

• Designed for research involving sensitive data types
• Access to large compute capacity
• Access to GPU's for intense machine learning workflows
• Enterprise grade hardware and software for reliability
• Located in enterprise data center to provide cushion for cooling and power issues.
• Support for a variety of workloads including container orchestration and virtual machines

Cluster Hardware Types

RRCE Environment

The Regulated Research Computational Environment (RRCE) is built through a partnership between ¹ÏÉñÍø, EVMS and Sentara. It provides a virtual lab environment for computation and storage of regulated data sets including CUI and HIPAA. Capabilities range from high-capacity storage to cutting edge GPUs to accelerate AI/ML research, data science and HPC. The environment is built on the TiCrypt software and provides a secure interface to transfer data and manage research projects in multiple security enclaves with disparate regulatory requirements.

Features of RRCE

• High-speed connectivity between ¹ÏÉñÍø, VMASC and EVMS
• Hyperconverged virtual environment
• 240 computation cores
• 12 Nvidia A100 GPUs
• Secure, segmented network infrastructure
• NIST 800-171, and CMMC level 2 compliance

Types of protected data

• General sensitive data (ex: business confidential)
• Regulated sensitive data:
  • FERPA (educational data, e.g. student records)
  • Personal Health Information (regulated by HIPAA)
  • Controlled Unclassified Information (CUI, NIST 800-171)
  • ITAR data (export-controlled data)

Features

• Linux and Windows virtual machines built on demand from golden images
• Persistent, encrypted data storage and sharing via tiCrypt's Vault and Drives
• Audit logging and alerting
• Data labeling for security classification
• Secure data ingestion via forms and sftp

Research Software

The software packages installed on the compute clusters is continuously changing with researchers needs.

• Physics/chemistry: Espresso, gromacs
• Biology: BLAST, Bioperl, migrate-n
• Engineering: OpenFOAM
• Statistics/math: R, Pandas, octave
• Scripting: python, perl, ruby, Java, ROOT
• Visualization: VTK, ParaView

• Chemistry: Gaussian, Molpro, VASP, amber
• Math: MATLAB
• Biology: CLC Bio
• Engineering/physics: COMSOL, ANSYS
• Statistics/business: SAS

• Compilers: Intel, PGI, GNU (Fortran, C, C++), Clang, NVIDIA (CUDA)
• Libraries: math (MKL, LAPACK, fftw3), machine learning (TensorFlow, PyTorch, Caffe, scikit-learn)
• Parallel programming (MPI, Charm++)
• Debuggers, profilers (GDB, TotalView, PAPI)

These are representative lists only. The complete list is much longer and keeps growing!
If there is software you need to use that is not on this list please contact us and we will install it for you.

Windows:

• Putty is a lightweight ssh client used for command line access to the clusters.
• RDP is recommended for graphical access to cluster resources.Ìý

Mac/Linux:

• Mac and Linux systems typically have an ssh client built in. You can also download the Microsoft RDP client for graphical access.

File Transfer Tools

We recommend to transfer files to and from the cluster. It's easy to use and works across multiple platforms. After you download and install the application, it needs to be configured to connect to the cluster (either Turing or Wahab).