[ https://issues.apache.org/jira/browse/LUCENE-7745?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17028416#comment-17028416 ]
Rinka Singh commented on LUCENE-7745: ------------------------------------- NDEBUG/Optimized version for Quadro 2000 GPU (192 cores) + Intel Dual Core + Kubuntu 14.04, CUDA 7.5: 350.774 sec.. I think its time to release the code... > 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. -- This message was sent by Atlassian Jira (v8.3.4#803005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@lucene.apache.org For additional commands, e-mail: issues-h...@lucene.apache.org