About the HPC Center

The High Performance Computing Center at Stanford University was founded to provide high performance computing resources & services to enable computationally-intensive research within the School of Engineering.

The mission of the High Performance Computing Center (HPCC) at Stanford University is to support the research efforts of scientists performing sponsored research. In addition, HPCC provides support for credit-based courses within the School of Engineering. To accomplish this, HPCC engages in the following activities:

  • Evaluates, acquires and deploys high performance computing resources, including both computing systems and software
  • Offers training workshops, seminars, and lectures in academic classes to educate and prepare new users of these resources provides expert consulting and technical documentation to assist researchers in using these resources effectively
  • Conducts research and testing of new computational techniques and technologies that enhance the capabilities of high performance computing resources
  • Collaborate with national labs, computing centers and HPC vendors to enhance the capabilities of the resources in use at the center

Resources and Support
The High Performance Computing Center deploys and operates the computational infrastructure enabling research activities of faculty, staff and students at Stanford University. HPCC also provides consulting, technical documentation and training for users of these resources. HPCC resources include:

  • High Performance Computing (HPC) systems of a variety of architectures to enable larger simulations, analyses and faster computation times than are possible using computers available to individual researchers
  • Advanced Scientific Visualization resources including computing systems with high performance graphics hardware, large displays, display walls, and high-end pre/post processing facilities to enable large data analysis and promote discovery
  • Massive Data Storage/Archival systems to store the vast quantities of data that result from performing simulations on HPC systems and developing visualizations of large data sets