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UTRC Characteristics

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  • High-performance computing (HPC), including distributed and shared memory systems, for large-scale simulations and analyses
  • Massive, flexible, high-speed data storage, which makes use of virtual environments and is capable of storing extremely large data sets such as sequencing or imaging data
  • Visualization systems and displays, including graphics clusters and tiled displays, that can render and depict images from terabytes of data
  • Servers (and virtual machines) for hosting applications that provide access (e.g. web-based) to data, resources, workflows, software, and documentation
  • Network infrastructure that connects central resources and institution resources with low latency and high transfer speeds to make location irrelevant
  • "Green" technologies that minimize operational cost
  • Failover systems to ensure business continuity


  • System software that ensures reliable, efficient operations of the systems
  • Programming, debugging, and optimization tools that enable researchers to develop applications that perform and scale
  • Optimized scientific applications software that enables domain researchers to focus on the science rather than the computing technologies and interfaces that enable researchers to use these applications easily from their labs, offices, and remote locations

Data Collections

  • Information-rich databases that publish valuable scientific data from instruments for reuse and broader usage.  Some key examples include
    • Multi-center, randomized clinical trials and epidemiologic cohort studies
    • Geosciences data collections that enable collaboration on weather, climate, and energy research
    • Libraries of data that can be used for simulations
  • Simulation data produced that enables verification and validation of new codes
  • Data management and collection tools to organize data
  • Leveraging library expertise around data management
  • Policies and support to ensure long-term availability of data archives for future research and to ensure reproducibility


  • Physical security of resources
  • Data and network security
  • Compliance with accepted federal and industry standards

Regulatory and Collaboration

  • Compliance with clinical standards accepted by potential outside partners in industry and governmental agencies such as the NIH and the VA
  • Partnership with the IRB to design operations that comply with privacy and consent requirements
  • Software
  • Leveraged buying power for distributed licenses
  • Community building collaboration tools and social networking
  • Cataloging of expertise and resources


  • Decisions for acquisitions, configurations, and locations of investments
  • Policies for granting access and priorities
  • Balancing of security against the need for access and flexibility
  • Clarification of intellectual property
  • Provision of ground rules that encourage participation and address data "ownership" issues.  Examine and redesign current policy that inhibits innovative use of proposed tools and resources

Human Capital

  • Expertise in computing and statistical methods
  • Training
  • Adoption
  • IT professionals
  • Library professionals
  • Software developers
  • Recruitment: technical and scientific