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 

> 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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