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Posted to dev@lucene.apache.org by "Adrien Grand (JIRA)" <ji...@apache.org> on 2018/06/28 16:07:00 UTC
[jira] [Commented] (LUCENE-7745) Explore GPU acceleration for
spatial search
[ https://issues.apache.org/jira/browse/LUCENE-7745?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16526467#comment-16526467 ]
Adrien Grand commented on LUCENE-7745:
--------------------------------------
David, I'm not sure this was meant to be specific to lucene/spatial, Mark only mentioned it as a way to conduct an initial benchmark? The main thing that we identified as being a potential candidate for integration with Cuda is actually BooleanScorer (BS1, the one that does scoring in bulk) based on previous comments?
> Explore GPU acceleration for spatial search
> -------------------------------------------
>
> Key: LUCENE-7745
> URL: https://issues.apache.org/jira/browse/LUCENE-7745
> Project: Lucene - Core
> Issue Type: Improvement
> Components: modules/spatial-extras
> Reporter: Ishan Chattopadhyaya
> Assignee: Ishan Chattopadhyaya
> Priority: Major
> Labels: gsoc2017, mentor
> Attachments: gpu-benchmarks.png
>
>
> There are parts of Lucene that can potentially be speeded up if computations were to be offloaded from CPU to the GPU(s). With commodity GPUs having as high as 12GB of high bandwidth RAM, we might be able to leverage GPUs to speed parts of Lucene (indexing, search).
> First that comes to mind is spatial filtering, which is traditionally known to be a good candidate for GPU based speedup (esp. when complex polygons are involved). In the past, Mike McCandless has mentioned that "both initial indexing and merging are CPU/IO intensive, but they are very amenable to soaking up the hardware's concurrency."
> I'm opening this issue as an exploratory task, suitable for a GSoC project. I volunteer to mentor any GSoC student willing to work on this this summer.
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