Texas Virtual Data Library (Texas ViDaL)

A Secure and Legally Compliant Data Infrastructure

Announcements

How To Use: click on the HowTo in the menu above.

Apply to use ViDaL (NOTE: You must be logged in to a TAMU account to apply):

Click here to fill out the application

Click here to print, sign, and email (admin@vidal.tamu.edu) the user agreement


IRB: You can refer to this computing infrastructure in the IRB application as TAMU ViDaL computing servers with following explanation:
  • TAMU ViDaL computing servers is securely maintained in the West Campus Data Center by the TAMU HPRC and meets compliance requirements approved by TAMU’s chief privacy officer

Are you looking for a collaborative computing environment that is easy to use and can handle data science projects with large RAM and GPUs ?

Texas Virtual Data Library (Texas ViDaL) computing servers are a new onsite free super computing infrastructure managed by TAMU HPRC and might be a good fit for your next data science project. If you have projects you want to put on ViDaL, please contact Dr. Hye-Chung Kum (kum at tamu dot edu) for more information.

What it offers

  • Both Windows and Linux OS are available
  • Large memory nodes (1.5TB & 192GB)
  • NVIDIA V100 GPUs
  • securely maintained in the West Campus Data Center by the TAMU HPRC and meets compliance requirements approved by TAMU’s chief privacy and security officers

Who might benefit

  • Undergraduates doing research in data science
  • Data science projects with staff that are not well trained in programming and linux
  • Research that would benefit from having a collaborative disk space to share data and programs
  • Data science projects that do not fit well with traditional high performance computing environments
  • Research that requires HIPAA compliance
  • Research that involves proprietary data with legal agreement (e.g., licensed data)

Types of Compliant Computing Available

  • Large RAM nodes: 4 nodes with 1.5TB Ram each
  • Regular RAM nodes: 16 nodes with 192GB Ram each
  • GPU nodes: 4 GPU nodes, each with 192 GB Ram and two NVIDIA V100 GPUs

Please acknowledge ViDaL whenever appropriate

  • “This work was supported in part by the Texas Virtual Data Library (ViDaL) funded by the Texas A&M University Research Development Fund”
  • Please report any proposals or papers that benefit from vidal to us over email (admin@vidal.tamu.edu). This is important for tracking and reporting purposes for future funding to keep vidal affordable to us.