[jira] [Commented] (LUCENE-7745) Explore GPU acceleration

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[jira] [Commented] (LUCENE-7745) Explore GPU acceleration

JIRA jira@apache.org

    [ https://issues.apache.org/jira/browse/LUCENE-7745?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15932568#comment-15932568 ]

David Smiley commented on LUCENE-7745:
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I have a question to us all.  (a) could whatever comes of this actually be contributed to Lucene itself given the likelihood of requiring native O.S. bindings (lets presume in spatial-extras as it seems this is the only module that can have an external dependency), and (b) does that matter for GSOC or to the expectations of the contributor?  If (a) is a "no", we need to be honest up front with the contributor.  I know in the past Solr has been denied off-heap filters that would have required a un-pure Java approach.  A native binding would be another degree of un-purity :-)

> Explore GPU acceleration
> ------------------------
>
>                 Key: LUCENE-7745
>                 URL: https://issues.apache.org/jira/browse/LUCENE-7745
>             Project: Lucene - Core
>          Issue Type: Improvement
>            Reporter: Ishan Chattopadhyaya
>              Labels: gsoc2017, mentor
>
> 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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