Communication optimization for medical image reconstruction algorithms. Hoefler, T., Schellmann, M., Gorlatch, S., & Lumsdaine, A. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5205 LNCS:75-83, 2008.
Communication optimization for medical image reconstruction algorithms [link]Website  doi  abstract   bibtex   
This paper presents experiences and results obtained in optimizing the parallel communication performance of a production-quality medical image reconstruction application. The fundamental communication operations in the application's principal algorithm are collective reductions. The overhead of these operations was reduced by transforming the algorithm to overlap its computation and communication. Several different approaches to communication progress were studied, both user-directed and asynchronous. Experimental results comparing the new approach to the previous implementation show overall application performance improvements of up to 8%, when run on 32 nodes. © 2008 Springer-Verlag Berlin Heidelberg.
@article{
 title = {Communication optimization for medical image reconstruction algorithms},
 type = {article},
 year = {2008},
 keywords = {Application performances; Communication operation,Applications; Image processing; Image reconstructi,Communication},
 pages = {75-83},
 volume = {5205 LNCS},
 websites = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-56449110627&doi=10.1007%2F978-3-540-87475-1_15&partnerID=40&md5=a836ee27c66abef2c2c2931cebf300ca},
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 notes = {cited By 6; Conference of 15th European PVM/MPI Users' Group Meeting, EuroPVM/MPI 2008 ; Conference Date: 7 September 2008 Through 10 September 2008; Conference Code:74258},
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 abstract = {This paper presents experiences and results obtained in optimizing the parallel communication performance of a production-quality medical image reconstruction application. The fundamental communication operations in the application's principal algorithm are collective reductions. The overhead of these operations was reduced by transforming the algorithm to overlap its computation and communication. Several different approaches to communication progress were studied, both user-directed and asynchronous. Experimental results comparing the new approach to the previous implementation show overall application performance improvements of up to 8%, when run on 32 nodes. © 2008 Springer-Verlag Berlin Heidelberg.},
 bibtype = {article},
 author = {Hoefler, T and Schellmann, M and Gorlatch, S and Lumsdaine, A},
 doi = {10.1007/978-3-540-87475-1_15},
 journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}
}

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