High-Performance Blob-Based Iterative Reconstruction of Electron Tomography on Multi-GPUs
Three-dimensional (3D) reconstruction of electron tomography (ET) has emerged as a leading technique to elucidate the molecular structures of complex biological specimens. Blob-based iterative methods are advantageous reconstruction methods for 3D reconstruction of ET, but demand huge computational costs. Multiple Graphic processing units (multi-GPUs) offer an affordable platform to meet these demands, nevertheless, are not efficiently used owing to a synchronous communication scheme and the limited available memory of GPUs. We propose a multilevel parallel scheme combined with an asynchronous communication scheme and a blob-ELLR data structure. The asynchronous communication scheme is used to minimize the idle GPU time. The blob-ELLR data structure only needs nearly 1/16 of the storage space in comparison with ELLPACK-R (ELLR) data structure and yields significant acceleration. Experimental results indicate that the multilevel parallel scheme allows efficient implementations of 3D reconstruction of ET on multi-GPUs, without loss any resolution.
Keywordselectron tomography (ET) three-dimensional (3D) reconstruction iterative methods blob multi-GPUs
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- 6.Andreyev, A., Sitek, A., Celler, A.: Acceleration of Blob-based Iterative Reconstruction Algorithm using Tesla GPU. IEEE NSS/MIC (2009)Google Scholar
- 8.NVIDIA, CUDA Programming Guide (2008), http://www.nvidia.com/cuda
- 14.Vazquez, F., Garzon, E.M., Fernandez, J.J.: Accelerating Sparse Matrix-vector Product with GPUs. In: Proceedings of CMMSE 2009, pp. 1081–1092 (2009)Google Scholar