WikiSysop: Created page with "== Citation == Fu, J., Xu, J., Gan, L., Mao, T., Shen, Z., Wang, Y., Song, Z., Duan, X., Xue, W. and Yang, G. 2025. T2-RELION: Task Parallelism, Tensor Core Accelerated RELION for Cryo-EM 3D Reconstruction. Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (2025), 2186–2202. == Abstract == Cryo-electron microscopy (cryo-EM) is a key technique for structural biology, but its computational efficiency, particul..."

2025-11-21T11:07:57Z

Created page with "== Citation == Fu, J., Xu, J., Gan, L., Mao, T., Shen, Z., Wang, Y., Song, Z., Duan, X., Xue, W. and Yang, G. 2025. T2-RELION: Task Parallelism, Tensor Core Accelerated RELION for Cryo-EM 3D Reconstruction. Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (2025), 2186–2202. == Abstract == Cryo-electron microscopy (cryo-EM) is a key technique for structural biology, but its computational efficiency, particul..."

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== Citation ==

Fu, J., Xu, J., Gan, L., Mao, T., Shen, Z., Wang, Y., Song, Z., Duan, X., Xue, W. and Yang, G. 2025. T2-RELION: Task Parallelism, Tensor Core Accelerated RELION for Cryo-EM 3D Reconstruction. Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (2025), 2186–2202.

== Abstract ==

Cryo-electron microscopy (cryo-EM) is a key technique for structural
biology, but its computational efficiency, particularly during
3D reconstruction, remains a bottleneck.We introduce T2-RELION,
a highly optimized version of RELION for cryo-EM 3D reconstruction
on CPU-GPU platforms. RELION is a widely used open-source
package in the cryo-EM community. We identify and resolve key
inefficiencies in RELION’s parallelization strategy and memory
management by proposing task parallelism and a three-phase GPU
memory management strategy. Furthermore, we leverage Tensor
Cores to accelerate the hot-spot kernel for difference calculation,
employing an advanced pipelining strategy to hide latency and enable
thread-block-level data reuse. On a quad-A100 GPU machine,
performance evaluations demonstrate that T2-RELION outperforms
RELION 4.0. For the hot-spot kernel, our optimizations achieve 1.90-
23.7 times speedup. For the whole application using CNG and Trpv1
datasets, we observe 3.86 times and 2.68 times speedups, respectively.

== Keywords ==

== Links ==

https://dl.acm.org/doi/full/10.1145/3712285.3759824

== Related software ==

== Related methods ==

== Comments ==

2025Fu T2Relion - Revision history