Parallelizing the cryo‐EM structure determination in THUNDER using GPU cluster
Abstract Electron cryo‐microscopy (cryo‐EM) is a powerful tool utilized by biologists for understanding the mysteries of life. However, obtaining high‐resolution 3D reconstructions from innumerable noisy images of macromolecules is an extremely complicated task, involving massive image analysis and...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-01-01
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| Series: | Engineering Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/eng2.12601 |
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| Summary: | Abstract Electron cryo‐microscopy (cryo‐EM) is a powerful tool utilized by biologists for understanding the mysteries of life. However, obtaining high‐resolution 3D reconstructions from innumerable noisy images of macromolecules is an extremely complicated task, involving massive image analysis and calculation on a computing cluster. Although extensive efforts have been made for improving the computational efficiency, methods for completely utilizing the computing resources are still challenging for modern cryo‐EM programs. Here, we designed a new computing approach specialized for GPU to optimize and maximize the computing power of a single GPU, multiple GPU, and the GPU cluster, highlighted by a well‐designed cache structure and mixed computing precision of single‐precision and double‐precision. Our approaches achieved remarkable improvement in performance and linear scalability. At an identical cost of the hardware, three‐fold more speed‐up was achieved. The average parallel efficiency can increase up to 84% when multiple GPU configurations are parallelized. |
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| ISSN: | 2577-8196 |