GTC 2020: High Throughput Cryo-Electron Microscopy and Cryo-Electron Tomography Powered by GPU at the University of California, San Francisco
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High Throughput Cryo-Electron Microscopy and Cryo-Electron Tomography Powered by GPU at the University of California, San Francisco
Shawn Zheng, Howard Hughes Medical Institute, University of California San Francisco
As early as in 2009, GPU-based computing was introduced at the University of California, San Francisco (UCSF) to reconstruct electron tomographic volumes. Today, 10 years later, high-resolution cryo-electron microscopy (CryoEM) and cryo-electron tomography (CryoET) powered by state-of-the-art GPU technology are routinely used worldwide in structural biology. We'll present the development of GPU-based applications at UCSF to solve critical challenges in CryoEM and CryoET — namely, beam-induced motion, cryoET alignment, and deep-learning based de-noising of cryoEM low-dose images. You should be familiar with back- and forward-projections, Fourier Transforms, C++, and CUDA programming.