Designed especially for neurobiologists, FluoRender is an interactive tool for multi-channel fluorescence microscopy data visualization and analysis.
Deep brain stimulation
BrainStimulator is a set of networks that are used in SCIRun to perform simulations of brain stimulation such as transcranial direct current stimulation (tDCS) and magnetic transcranial stimulation (TMS).
Developing software tools for science has always been a central vision of the SCI Institute.
Dr. Alan Humphrey

Dr. Alan Humphrey - Research Computer Scientist

WEB 4819
phone (801) 585-5090
fax (801) 585-6513
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supervisor Dr. Martin Berzins

My Publications

My Homepage


Dr. Alan Humphrey received his Ph.D. in Computer Science from the University of Utah in 2019, and a B.Sc. in Computer Science from the University of Utah in 2011. During the time of his doctoral degree, he was also lead developer for the Uintah Computational Framework. His doctoral research focused on Scalable Asynchronous Many-Task Runtime Solutions to Globally Coupled Problems, specifically, the development of a scalable GPU-based radiation transport model to run at full-scale on the heterogeneous, DOE Titan system in preparation for machines like DOE Summit and NNSA Lassen. This work is driven by the target problem for the Utah Carbon-Capture Multidisciplinary Simulation Center, an NNSA, PSAAP II Center, which aims to use simulation science at petascale and eventually exascale to accelerate the design of the next generation of clean coal boilers that will improve clean coal technologies.

Current Responsibilities

Dr. Humphrey is currently a Contractor for Sandia National Laboratories where he works with the Kokkos C++ Performance Portability Programming EcoSystem and the Application Performance Team to develop and analyze performant software solutions for current and next generation HPC platforms.

Research Interests

  • Asynchronous Many-Task (AMT) Runtime Systems
  • Performance Portability
  • Parallel Programming Models
  • Large-scale High Performance Computing (HPC)
  • Emerging and Future HPC Architectures
  • Message Passing Interface (MPI)
  • GPU Computing