Optimal Multi-Image Processing Streaming Framework on Parallel Heterogeneous Systems

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dc.contributor.authorHa, Linh K.en_US
dc.contributor.authorKrüger, Jensen_US
dc.contributor.authorComba, Joaoen_US
dc.contributor.authorJoshi, Sarangen_US
dc.contributor.authorSilva, Cláudio T.en_US
dc.contributor.editorTorsten Kuhlen and Renato Pajarola and Kun Zhouen_US
dc.date.accessioned2014-01-26T16:57:03Z
dc.date.available2014-01-26T16:57:03Z
dc.date.issued2011en_US
dc.description.abstractAtlas construction is an important technique in medical image analysis that plays a central role in understanding the variability of brain anatomy. The construction often requires applying image processing operations to multiple images (often hundreds of volumetric datasets), which is challenging in computational power as well as memory requirements. In this paper we introduce MIP, a Multi-Image Processing streaming framework to harness the processing power of heterogeneous CPU/GPU systems. In MIP we introduce specially designed streaming algorithms and data structures that provides an optimal solution for out-of-core multi-image processing problems both in terms of memory usage and computational efficiency. MIP makes use of the asynchronous execution mechanism supported by parallel heterogeneous systems to efficiently hide the inherent latency of the processing pipeline of out-of-core approaches. Consequently, with computationally intensive problems, the MIP out-of-core solution could achieve the same performance as the in-core solution. We demonstrate the efficiency of the MIP framework on synthetic and real datasets.en_US
dc.description.seriesinformationEurographics Symposium on Parallel Graphics and Visualizationen_US
dc.identifier.isbn978-3-905674-32-3en_US
dc.identifier.issn1727-348Xen_US
dc.identifier.urihttps://doi.org/10.2312/EGPGV/EGPGV11/001-010en_US
dc.publisherThe Eurographics Associationen_US
dc.titleOptimal Multi-Image Processing Streaming Framework on Parallel Heterogeneous Systemsen_US
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EGPGV11: Eurographics Symposium on Parallel Graphics and Visualization