Using MPI: portable parallel programming with the message-passing interface
Using MPI: portable parallel programming with the message-passing interface
High Performance Cluster Computing: Programming and Applications
High Performance Cluster Computing: Programming and Applications
Parallel Optimization: Theory, Algorithms and Applications
Parallel Optimization: Theory, Algorithms and Applications
Applying scheduling and tuning to on-line parallel tomography
Proceedings of the 2001 ACM/IEEE conference on Supercomputing
HCW '00 Proceedings of the 9th Heterogeneous Computing Workshop
The Telescience Portal for advanced tomography applications
Journal of Parallel and Distributed Computing - Special issue on computational grids
Electron tomography of complex biological specimens on the Grid
Future Generation Computer Systems
Parameter optimization in 3D reconstruction on a large scale grid
Parallel Computing
High performance noise reduction for biomedical multidimensional data
Digital Signal Processing
Efficient parallel implementation of iterative reconstruction algorithms for electron tomography
Journal of Parallel and Distributed Computing
Data neighboring in local load balancing operations
ICCOMP'05 Proceedings of the 9th WSEAS International Conference on Computers
International Journal of High Performance Computing Applications
High-performance Blob-based iterative reconstruction of electron tomography on multi-GPUs
ISBRA'11 Proceedings of the 7th international conference on Bioinformatics research and applications
Evaluation of parallel paradigms on anisotropic nonlinear diffusion
Euro-Par'06 Proceedings of the 12th international conference on Parallel Processing
A performance prediction model for tomographic reconstruction in structural biology
VECPAR'04 Proceedings of the 6th international conference on High Performance Computing for Computational Science
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Electron microscope tomography has emerged as the leading technique for structure determination of cellular components with a resolution of a few nanometers, opening up exciting perspectives for visualizing the molecular architecture of the cytoplasm. This work describes and analyzes the parallelization of tomographic reconstruction algorithms for their application in electron microscope tomography of cellular structures. Efficient iterative algorithms that are characterized by a fast convergence rate have been used to tackle the image reconstruction problem. The use of smooth basis functions provides the reconstruction algorithms with an implicit regularization mechanism, very appropriate for highly noisy conditions such as those present in high-resolution electron tomographic studies. Parallel computing techniques have been applied so as to face the computational requirements demanded by the reconstruction of large volumes. An efficient domain decomposition scheme has been devised that leads to a parallel approach with capabilities of interprocessor communication latency hiding. The combination of efficient iterative algorithms and parallel computing techniques have proved to be well suited for the reconstruction of large biological specimens in electron tomography, yielding solutions in reasonable computational times. This work concludes that parallel computing will be the key to afford high-resolution structure determination of cells, so that the location of molecular signatures in their native cellular context can be made a reality.