Over at the Cuda Spotlight, Calissa Cole writes that Dr. Michela Taufer at the University of Delaware is rethinking application algorithms to fit on the GPU architecture in order to get the most out of its computing power, while preserving the scientific accuracy of the simulations.
It’s not about how GPUs help my work but rather how GPUs help me to fulfill my personal and professional mission of helping scientists discover science through high-performance computing. I will never forget the excitement of my collaborator Sandeep Patel when we were able to observe the exploration activity of small peptides on a large membrane surface. It was known that the phenomenon existed but it was not observable previously because of the complexity of simulating membranes at large space and time scales. But we did it! We could clearly identify the location on the membrane when the peptide was external to the membrane (red dots on the peptide-membrane surface in Figure 2) versus when the peptide was directly interacting with the lipid bilayer atoms (blue dots on the peptide-membrane surface in Figure 2). This would have not been possible without GPUs, which provided us with the computing power to cope with the large length and time scales for this type of molecular simulation.
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