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https://issues.apache.org/jira/browse/LUCENE-7745?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17036124#comment-17036124
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Rinka Singh edited comment on LUCENE-7745 at 2/13/20 10:47 AM:
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OK. Here's the basic histogramming code:
[https://github.com/rinka-meltiron/MiLib]
Looking forward to feedback.
One correction to my inputs in the previous posts. The test file was 2.5MB of
text, not 5 MB of text. I'm sorry, I can't include that file here as it is
copywrited... I have put other files that I've included for testing.
was (Author: rinka):
OK. Here's the basic histogramming code:
[https://github.com/rinka-meltiron/MiLib]
Looking forward to feedback.
> Explore GPU acceleration
> ------------------------
>
> Key: LUCENE-7745
> URL: https://issues.apache.org/jira/browse/LUCENE-7745
> Project: Lucene - Core
> Issue Type: Improvement
> Reporter: Ishan Chattopadhyaya
> Assignee: Ishan Chattopadhyaya
> Priority: Major
> Labels: gsoc2017, mentor
> Attachments: TermDisjunctionQuery.java, 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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