by Calisa Cole

Joshua Adelman is more than your average student.  He’s studying biological phenomena to better understand common diseases such as diabetes and epilepsy, leveraging the computational power of GPUs. We recently discovered his work through the Grabe Lab at the University of Pittsburgh, and were particularly interested when we learned he’s funding his project through peer-reviewed, “crowd-source” funding organization, FundScience. We caught up with Joshua, and had a chance to interview him to learn more:

NVIDIA: Joshua, tell us about your research.


    : I am interested in understanding how proteins that sit in the cell membrane selectively transport small molecules across the membrane. Specifically, I study two transporters – one removes a neurotransmitter from the synapse and is critical in proper nervous system function; the other is responsible for absorption of sugar in the intestines and kidneys. Both are potential targets for treating a number of diseases including ALS, epilepsy and type 2 diabetes.

Credit Thomas Harper Joshua Adelman (seated) with advisor Michael Grabe

NVIDIA: How are you leveraging GPU computing?


      : I use molecular dynamics to simulate these proteins to understand how structural changes in each facilitate transport. There has been considerable effort over the last couple of years by several groups to use GPUs to accelerate these types of calculations. The initial results are quite promising. I’m piggybacking off of one of these efforts, the


    API which provides CUDA and OpenCL implementations of key algorithms necessary to run molecular dynamics simulations.

Molecular model of a glutamate transporterMolecular model of a glutamate transporter

NVIDIA: What kind of results are you seeing?


    : For simple representations of the protein, we typically get a several hundred-fold increase in simulation throughput compared to a CPU implementation running on a single core. In this regard, GPUs running CUDA have been an enabling technology. They have allowed us to perform calculations that would have been completely unfeasible just a couple of years ago.

NVIDIA: Tell us about how your project is funded.


      : We are funded in part through


    , a non-profit organization that financially supports peer-reviewed pilot projects using crowd-sourced funding. My work was selected as one of the first three projects hosted on their site and the preliminary support has been a real boon in getting this project up and running.

NVIDIA: Who are some of your contributors and partners?


    : CDW and Paragon Micro have generously donated CUDA-based GPUs and the project has been supported by individuals with an interest in the science. I also have worked extensively with the University of Pittsburgh’s Center for Simulation and Modeling, which has made a strategic commitment to advancing GPGPU computing in various scientific disciplines on campus.

NVIDIA: How can people learn more about your research and how to donate?


      : My

FundScience project page can be found here

      and more information about our lab’s efforts can be found at


To read more about Joshua, see this recent article in Chemical and Engineering News.