On the Usage of GPUs for Efficient Motion Estimation in Medical Image Sequences.
Images are ubiquitous in biomedical applications from basic research to clinical practice. With the rapid increase in resolution, dimensionality of the images and the need for real-time performance in many applications, computational requirements demand proper exploitation of multicore architectures...
| Үндсэн зохиолчид: | , , , , |
|---|---|
| Формат: | Journal article |
| Хэл сонгох: | English |
| Хэвлэсэн: |
2011
|
| _version_ | 1826297516898910208 |
|---|---|
| author | Thiyagalingam, J Goodman, D Schnabel, J Trefethen, A Grau, V |
| author_facet | Thiyagalingam, J Goodman, D Schnabel, J Trefethen, A Grau, V |
| author_sort | Thiyagalingam, J |
| collection | OXFORD |
| description | Images are ubiquitous in biomedical applications from basic research to clinical practice. With the rapid increase in resolution, dimensionality of the images and the need for real-time performance in many applications, computational requirements demand proper exploitation of multicore architectures. Towards this, GPU-specific implementations of image analysis algorithms are particularly promising. In this paper, we investigate the mapping of an enhanced motion estimation algorithm to novel GPU-specific architectures, the resulting challenges and benefits therein. Using a database of three-dimensional image sequences, we show that the mapping leads to substantial performance gains, up to a factor of 60, and can provide near-real-time experience. We also show how architectural peculiarities of these devices can be best exploited in the benefit of algorithms, most specifically for addressing the challenges related to their access patterns and different memory configurations. Finally, we evaluate the performance of the algorithm on three different GPU architectures and perform a comprehensive analysis of the results. |
| first_indexed | 2024-03-07T04:32:50Z |
| format | Journal article |
| id | oxford-uuid:ceea162f-948c-4b08-95f2-05ddb5f9ff98 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T04:32:50Z |
| publishDate | 2011 |
| record_format | dspace |
| spelling | oxford-uuid:ceea162f-948c-4b08-95f2-05ddb5f9ff982022-03-27T07:38:47ZOn the Usage of GPUs for Efficient Motion Estimation in Medical Image Sequences.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:ceea162f-948c-4b08-95f2-05ddb5f9ff98EnglishSymplectic Elements at Oxford2011Thiyagalingam, JGoodman, DSchnabel, JTrefethen, AGrau, VImages are ubiquitous in biomedical applications from basic research to clinical practice. With the rapid increase in resolution, dimensionality of the images and the need for real-time performance in many applications, computational requirements demand proper exploitation of multicore architectures. Towards this, GPU-specific implementations of image analysis algorithms are particularly promising. In this paper, we investigate the mapping of an enhanced motion estimation algorithm to novel GPU-specific architectures, the resulting challenges and benefits therein. Using a database of three-dimensional image sequences, we show that the mapping leads to substantial performance gains, up to a factor of 60, and can provide near-real-time experience. We also show how architectural peculiarities of these devices can be best exploited in the benefit of algorithms, most specifically for addressing the challenges related to their access patterns and different memory configurations. Finally, we evaluate the performance of the algorithm on three different GPU architectures and perform a comprehensive analysis of the results. |
| spellingShingle | Thiyagalingam, J Goodman, D Schnabel, J Trefethen, A Grau, V On the Usage of GPUs for Efficient Motion Estimation in Medical Image Sequences. |
| title | On the Usage of GPUs for Efficient Motion Estimation in Medical Image Sequences. |
| title_full | On the Usage of GPUs for Efficient Motion Estimation in Medical Image Sequences. |
| title_fullStr | On the Usage of GPUs for Efficient Motion Estimation in Medical Image Sequences. |
| title_full_unstemmed | On the Usage of GPUs for Efficient Motion Estimation in Medical Image Sequences. |
| title_short | On the Usage of GPUs for Efficient Motion Estimation in Medical Image Sequences. |
| title_sort | on the usage of gpus for efficient motion estimation in medical image sequences |
| work_keys_str_mv | AT thiyagalingamj ontheusageofgpusforefficientmotionestimationinmedicalimagesequences AT goodmand ontheusageofgpusforefficientmotionestimationinmedicalimagesequences AT schnabelj ontheusageofgpusforefficientmotionestimationinmedicalimagesequences AT trefethena ontheusageofgpusforefficientmotionestimationinmedicalimagesequences AT grauv ontheusageofgpusforefficientmotionestimationinmedicalimagesequences |