Abstract
Electron tomography combines the acquisition of projection images through electronic microscope and techniques of tomographic reconstruction to allow structure determination of complex biological specimens. This kind of applications requires an extensive use of computational resources and considerable processing time because high resolution 3D reconstructions are demanded. The new tendency of high performance computing heads for hierarchical computational systems, where several shared memory nodes with multi-core CPUs are connected. In this work, we propose a hybrid parallel implementation for tomographic reconstruction of cellular specimens. Our results show that the balanced and adaptative algorithm allows an ideal speedup factor when large datasets are used.
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da Silva, M.L., Roca-Piera, J., Fernández, J.J. (2010). A Hybrid Parallel Approach for 3D Reconstruction of Cellular Specimens. In: de Leon F. de Carvalho, A.P., Rodríguez-González, S., De Paz Santana, J.F., Rodríguez, J.M.C. (eds) Distributed Computing and Artificial Intelligence. Advances in Intelligent and Soft Computing, vol 79. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14883-5_86
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DOI: https://doi.org/10.1007/978-3-642-14883-5_86
Publisher Name: Springer, Berlin, Heidelberg
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