BrainGrid+Workbench: Bringing High Performance Neural Simulation to the Desktop

Posted 1 year ago by Mike Stiber

School(s) : STEM
Primary PI Name : Mike Stiber
Interested? Contact Faculty Researcher by Email : stiber@uw.edu
Phone : 425-352-5280
Project/Faculty Website : http://faculty.washington.edu/stiber/
Research Location : UW Bothell
Project Goals : Neural networks are often viewed as smart algorithms that can harness parallel computing to perform intelligent tasks. Paradoxically, real — biological — neural networks are massively parallel, but so complex that it is difficult to map their requirements onto parallel computers. The BrainGrid project is building an open-source framework that will allow neuroscience researchers to move neural simulations from single-processor/single-core implementations to parallel, GPU (graphics processing unit) implementations. We have a beta version of our framework at git.io/braingrid, which we have used in our own research, simulating the development of 10,000 neurons over the course of several weeks. We have acquired the latest GPU hardware. We are now beginning to recruit external users. We then plan to work with those users to develop better documentation, wring out the bugs, and plan the next version.
Student Qualifications : Comfort programming in C++ or Java. Desire to learn lots of new things fast. Interest in moving beyond “big-O”, to think about the match between algorithm and machine architecture. Brain!!
Student Responsibilities : Learn some basic neuroscience. Learn some GPU programming basics. Learn about our framework and parallel algorithms. Attend weekly lab group meetings; help burn down the backlog. Test framework with new, simple, simulations. Improve our documentation. Engage in conversations about the next phase of BrainGrid development.
Number of Student Positions Available : 2
Additional information : For additional information, visit the Biocomputing Laboratory web site at http://depts.washington.edu/biocomp/ or the BrainGrid Github page at http://uwb-biocomputing.github.io/BrainGrid/.
Tags : computational neuroscience, neural networks, high performance computing, data visualization, software engineering

  • School(s) : STEM
  • Primary PI Name : Mike Stiber
  • Interested? Contact Faculty Researcher by Email : stiber@uw.edu
  • Phone : 425-352-5280
  • Project/Faculty Website : http://faculty.washington.edu/stiber/
  • Research Location : UW Bothell
  • Project Goals : Neural networks are often viewed as smart algorithms that can harness parallel computing to perform intelligent tasks. Paradoxically, real — biological — neural networks are massively parallel, but so complex that it is difficult to map their requirements onto parallel computers. The BrainGrid project is building an open-source framework that will allow neuroscience researchers to move neural simulations from single-processor/single-core implementations to parallel, GPU (graphics processing unit) implementations. We have a beta version of our framework at git.io/braingrid, which we have used in our own research, simulating the development of 10,000 neurons over the course of several weeks. We have acquired the latest GPU hardware. We are now beginning to recruit external users. We then plan to work with those users to develop better documentation, wring out the bugs, and plan the next version.
  • Student Qualifications : Comfort programming in C++ or Java. Desire to learn lots of new things fast. Interest in moving beyond “big-O”, to think about the match between algorithm and machine architecture. Brain!!
  • Student Responsibilities : Learn some basic neuroscience. Learn some GPU programming basics. Learn about our framework and parallel algorithms. Attend weekly lab group meetings; help burn down the backlog. Test framework with new, simple, simulations. Improve our documentation. Engage in conversations about the next phase of BrainGrid development.
  • Number of Student Positions Available : 2
  • Additional information : For additional information, visit the Biocomputing Laboratory web site at http://depts.washington.edu/biocomp/ or the BrainGrid Github page at http://uwb-biocomputing.github.io/BrainGrid/.
  • Tags : computational neuroscience, neural networks, high performance computing, data visualization, software engineering