GPU-enabled FREALIGN: Accelerating single particle 3D reconstruction and refinement in Fourier space on graphics processors
Open accessAbstract
Among all the factors that determine the resolution of a 3D reconstruction by single particle electron cryo-microscopy (cryoEM), the number of particle images used in the dataset plays a major role. More images generally yield better resolution, assuming the imaged protein complex is conformationally and compositionally homogeneous. To facilitate processing of very large datasets, we modified the computer program, FREALIGN, to execute the computationally most intensive procedures on Graphics Processing Units (GPUs). Using the modified program, the execution speed increased between 10 and 240-fold depending on the task performed by FREALIGN. Here we report the steps necessary to parallelize critical FREALIGN subroutines and evaluate its performance on computers with multiple GPUs.
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Feng ve diğerlerinin çalışmasında hareket ve yön doğrulama ile görüntü geriçatmada GPU kullanılmakta ve 6 kata kadar hızlanma elde edilmiştir.
“Bu çalışmada hareket ve yön doğrulama ile görüntü geriçatmada GPU kullanılmaktadır. Gerçekleştirilen çalışmada 6 kata kadar hızlanma elde edilmiştir.”
From GPU Programlamada CUDA Platformu Kullanılan Paralel Görüntü İşleme Çalışmalarının İncelenmesi (2020) · cites this paper as [32]
The Introduction and Conclusion report GPU-accelerated search, refinement and 3D reconstruction, supporting the reconstruction portion of the claim. They report approximately 10-fold acceleration for search and refinement and 240-fold for reconstruction—not a maximum of 6-fold. The cited passages do not describe motion correction. (LLM, conf=0.88)
Experimental — accuracy not yet measuredFeng ve diğerleri [32] 2013 yılında görüntü geriçatmada GPU'yu farklı bir kütüphane üzerinde kullanmışlardır; PROPELLER klinik uygulamalarda veri ve hareket doğrulama metotlarını kullanarak görüntü geriçatma gerçekleştiren bir sistemdir.
“Feng ve diğerleri [32] 2013 yılında yaptıkları çalışmada görüntü geriçatmada GPU'yu farklı bir kütüphane üzerinde kullanmışlardır. PROPELLER klinik uygulamalarda veri ve hareket doğrulama metotlarını kullanarak görüntü geriçatma gerçekleştiren bir sistemdir.”
From GPU Programlamada CUDA Platformu Kullanılan Paralel Görüntü İşleme Çalışmalarının İncelenmesi (2020) · cites this paper as [32]
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References 17 · Cited by 45
- Authors
- Li, X., Grigorieff, N., & Cheng, Y.
- Affiliations
- University of California, San Francisco (US)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Cheng, Yifan
- Venue
- Journal of Structural Biology
- Publisher
- Elsevier BV
- Published
- 2010-12
- Volume
- 172
- Issue
- 3
- Pages
- 407-412
- ISSN
- 1047-8477 (ISSN-L)
- PMC
- PMC2964447
- OpenAlex
- W1973838566
- Cited by
- 45
- References
- 17
- Citations by year
- 2023: 1 · 2022: 1 · 2021: 2 · 2020: 1 · 2019: 4 · 2018: 2 · 2017: 3 · 2016: 9 · 2015: 6 · 2014: 1 · 2013: 8 · 2012: 6
- FWCI
- 2.73
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Structural Biology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- NIH (R01GM082893, 1S10RR026814-01, P50GM082250)
- UCSF Program for Breakthrough Biomedical Research
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Advanced Electron Microscopy Techniques and Applications
- Physical Sciences › Computer Science › Hardware and Architecture › Parallel Computing and Optimization Techniques
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Keywords
- GPU acceleration, cryo-electron microscopy, parallel computing, multiple GPUs, speedup
- MeSH terms
- Image Processing, Computer-Assisted, Cryoelectron Microscopy, Imaging, Three-Dimensional
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