of a release at work and also my night time job (this).
> Explore GPU acceleration
>
>
> Key: LUCENE-7745
> URL: https://issues.apache.org/jira/browse/LUCENE-7745
> Project: Lucene - Core
> Issue Type:
ote}
Took a quick look - they are all priced products. I will take a look at
researchgate sometime.
I apologize but I may not be very responsive in the next month or so as we are
in the middle of a release at work and also my night time job (this).
> Explore GPU
togram bin at the
same time.
> Explore GPU acceleration
>
>
> Key: LUCENE-7745
> URL: https://issues.apache.org/jira/browse/LUCENE-7745
> Project: Lucene - Core
> Issue Type: Improvement
>
trying to
learn.
> Explore GPU acceleration
>
>
> Key: LUCENE-7745
> URL: https://issues.apache.org/jira/browse/LUCENE-7745
> Project: Lucene - Core
> Issue Type: Improvement
>Report
... In the meantime, if you want me to review
documents/design/thoughts/anything, please feel free to mail them to me at:
rinka (dot) singh (at) gmail. At least ping me - I really don't look at
the Apache messages and would probably miss something...
> Explore GPU accelerat
.
Hope this helps... In the meantime, if you want me to review
documents/design/thoughts/anything, please feel free to mail them to me at:
rinka (dot) singh (at) gmail. At least ping me - I really don't look at
the Apache messages and would probably miss something...
> Explore
to contribute back whatever we end up doing as a part of the project
> Explore GPU acceleration
>
>
> Key: LUCENE-7745
> URL: https://issues.apache.org/jira/browse/LUCENE-7745
> Project: Lucene - Core
> Is
of the CPU (I'll keep multi-GPU and multi
threading to use all CPUs in mind but implementing that will be a separate step
altogether).
Goal: Look at speed difference between an Index generated on the CPU vs GPU for
just this.
We can build from there...
Thoughts please...
> Explore GPU accelerat
a speed up too.
bq. How many AWS instances would usually be used for searching through ~140GB
sized inverted index
Hard to tell, it depends on your search load, how expensive queries are, etc.
> Explore GPU acceleration
>
>
> Key:
will be less than 140GB - I assume 8 GPUs
was (Author: rinka):
A few questions. How critical is the inverted index to the user experience?
What happens if the inverted index is speeded up?
> Explore GPU acceleration
>
>
> Key:
to the user experience?
What happens if the inverted index is speeded up?
> Explore GPU acceleration
>
>
> Key: LUCENE-7745
> URL: https://issues.apache.org/jira/browse/LUCENE-7745
> Project: Lucene - Core
>
that BooleanScorer might be one
scorer that could benefit from GPU acceleration as it scores large blocks of
documents at once. I just attached a specialization of a disjunction over term
queries that should make it easy to experiment with Cuda, see the TODO in the
end on top of the computeScores
.
{quote}That said Mike initially mentioned that BooleanScorer might be one
scorer that could benefit from GPU acceleration as it scores large blocks of
documents at once. I just attached a specialization of a disjunction over term
queries that should make it easy to experiment with Cuda, see
if the code is in dev state.
Would you have written up something to describe what you are doing?
> Explore GPU acceleration
>
>
> Key: LUCENE-7745
> URL: https://issues.apache.org/jira/browse/LUCENE-7745
> Project:
ore GPU acceleration
>
>
> Key: LUCENE-7745
> URL: https://issues.apache.org/jira/browse/LUCENE-7745
> Project: Lucene - Core
> Issue Type: Improvement
>Reporter: Ishan Chattopadhyaya
>
/Cyber Monday support schedule).
> Explore GPU acceleration
>
>
> Key: LUCENE-7745
> URL: https://issues.apache.org/jira/browse/LUCENE-7745
> Project: Lucene - Core
> Issue Type: Improvement
>
scorer that could
benefit from GPU acceleration as it scores large blocks of documents at once. I
just attached a specialization of a disjunction over term queries that should
make it easy to experiment with Cuda, see the TODO in the end on top of the
{{computeScores}} method.
> Explore
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Adrien Grand updated LUCENE-7745:
-
Attachment: TermDisjunctionQuery.java
> Explore GPU accelerat
like, I can write a brief (one or two paras) description of what is
possible for indexing, searching, filtering (with zero knowledge of Lucene of
course) to start off...
Your thoughts please...
> Explore GPU acceleration
>
>
> Key:
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David Smiley updated LUCENE-7745:
-
Component/s: (was: modules/spatial-extras)
Summary: Explore GPU acceleration
for all-things-GPU, if that makes sense?
> Explore GPU acceleration for spatial search
> ---
>
> Key: LUCENE-7745
> URL: https://issues.apache.org/jira/browse/LUCENE-7745
> Project: Lucene -
this was about BooleanScorer
or postings or something and then low and behold it's spatial -- and then I
thought this is so non-obvious by the issue title. So I thought it'd do a
little JIRA gardening.
> Explore GPU acceleration for spatial sea
for that. I'll let
Ishan decide how he wants to manage this issue, I'm personally fine either way,
I'm mostly following. :) It just caught me by surprise since I was under the
impression that we were still exploring which areas might benefit from GPU
acceleration.
> Explore GPU accelerat
to go in a new issue specific to
spatial.Accelerating Haversine calculations sounds way different to me than
BooleanScorer stuff; no?
> Explore GPU acceleration for spatial search
> ---
>
> Key: LUCENE-7745
>
/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 accelerat
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David Smiley updated LUCENE-7745:
-
Summary: Explore GPU acceleration for spatial search (was: Explore GPU
acceleration
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David Smiley updated LUCENE-7745:
-
Component/s: modules/spatial-extras
> Explore GPU accelerat
!
[0] - https://github.com/chatman/gpu-benchmarks
[1] -
https://github.com/apache/lucene-solr/blob/master/lucene/spatial-extras/src/test/org/apache/lucene/spatial/SpatialExample.java
> Explore GPU acceleration
>
>
> Key: LUCENE-7745
>
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Ishan Chattopadhyaya reassigned LUCENE-7745:
Assignee: Ishan Chattopadhyaya
> Explore GPU accelerat
-benchmarks
[1] -
https://github.com/apache/lucene-solr/blob/master/lucene/spatial-extras/src/test/org/apache/lucene/spatial/SpatialExample.java
> Explore GPU acceleration
>
>
> Key: LUCENE-7745
> URL: https://issues.apache.org/jir
-benchmarks
[1] -
https://github.com/apache/lucene-solr/blob/master/lucene/spatial-extras/src/test/org/apache/lucene/spatial/SpatialExample.java
> Explore GPU acceleration
>
>
> Key: LUCENE-7745
> URL: https://issues.apache.org/jir
/chatman/gpu-benchmarks
[1] -
https://github.com/apache/lucene-solr/blob/master/lucene/spatial-extras/src/test/org/apache/lucene/spatial/SpatialExample.java
> Explore GPU acceleration
>
>
> Key: LUCENE-7745
> URL: https://is
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Ishan Chattopadhyaya updated LUCENE-7745:
-
Attachment: gpu-benchmarks.png
> Explore GPU accelerat
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Ishan Chattopadhyaya updated LUCENE-7745:
-
Attachment: (was: Screenshot from 2018-06-27 15-33-37.png)
> Explore
://github.com/chatman/gpu-benchmarks
[1] -
https://github.com/apache/lucene-solr/blob/master/lucene/spatial-extras/src/test/org/apache/lucene/spatial/SpatialExample.java
> Explore GPU acceleration
>
>
> Key: LUCENE-7745
>
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Ishan Chattopadhyaya updated LUCENE-7745:
-
Attachment: Screenshot from 2018-06-27 15-33-37.png
> Explore GPU accelerat
/SpatialExample.java
> Explore GPU acceleration
>
>
> Key: LUCENE-7745
> URL: https://issues.apache.org/jira/browse/LUCENE-7745
> Project: Lucene - Core
> Issue Type: Improvement
>Report
will my proposal be checked?
> Explore GPU acceleration
>
>
> Key: LUCENE-7745
> URL: https://issues.apache.org/jira/browse/LUCENE-7745
> Project: Lucene - Core
> Issue Type: Improvement
>
itself so I
will do some working and so will the repository I build for lucene and work I
store there be checked by ASF?
And by whom will my proposal be checked?
> Explore GPU acceleration
>
>
> Key: LUCENE-7745
>
, but can
I start working still and I shall give you the link that has my working and if
it would be possible for you , you could show to the Apache Software Foundation
my works, will that be ok?
> Explore GPU acceleration
>
>
> Key:
to the Apache Software Foundation
my works, will that be ok?
> Explore GPU acceleration
>
>
> Key: LUCENE-7745
> URL: https://issues.apache.org/jira/browse/LUCENE-7745
> Project: Lucene - Core
> Is
. This is
not strictly necessary, but just throwing out an idea that might benefit you.
All the best and regards!
> Explore GPU acceleration
>
>
> Key: LUCENE-7745
> URL: https://issues.apache.org/jira/browse/LUCENE-7745
> Proj
the proposal
properly.
> Explore GPU acceleration
>
>
> Key: LUCENE-7745
> URL: https://issues.apache.org/jira/browse/LUCENE-7745
> Project: Lucene - Core
> Issue Type: Improvement
>Report
the scoring for that on the GPU). It seems you have not done so.
At this point, I don't think much can be done (just 2 hours to go for
submission). Wish you the best.
> Explore GPU acceleration
>
>
> Key: LUCENE-7745
>
, can you review it
again?
> Explore GPU acceleration
>
>
> Key: LUCENE-7745
> URL: https://issues.apache.org/jira/browse/LUCENE-7745
> Project: Lucene - Core
> Issue Type: Improvement
>
. Let me know if you want another
round of review, perhaps after you've addressed the current comments.
> Explore GPU acceleration
>
>
> Key: LUCENE-7745
> URL: https://issues.apache.org/jira/browse/LUCENE-7745
>
and
its too close, in the preparation I had almost missed the deadline for
application. OK so for the proposal my draft is here (you may comment on it and
I will do the needful)
https://docs.google.com/document/d/1HGxU1ZudNdAboj0s9WKTWJk3anbZm86JY-abaflXoEI/edit?usp=sharing
.
> Explore
with that is a plus.
(Just a suggestion that makes sense to me, and feel free to ignore: bullet
points work better than long paragraphs, even though the length of sentences
can remain the same)
> Explore GPU acceleration
>
>
> Key: LUCENE-7745
>
. speed observed when doing
>the same through the BooleanScorer. Preferably, on a large result set with the
>time for copying results and scores in and out of the device memory from/to
>the main memory included?
-Vikash
> Explore GPU acceleration
> ---
their licenses
jCuda happens to be MIT, which is, afaik, compatible with Apache license.
http://www.jcuda.org/License.txt
> Explore GPU acceleration
>
>
> Key: LUCENE-7745
> URL: https://issues.apache.org/jira/bro
(which in itself could be a sufficient GSoC project), one
can have stretch goals to try out other parts of Lucene to optimize (e.g.
spatial search).
> Explore GPU acceleration
>
>
> Key: LUCENE-7745
> URL: https://issues.
for
copying results and scores in and out of the device memory from/to the main
memory.
# Optimize step 2, if possible.
Once this is achieved (which in itself could be a sufficient GSoC project), one
can have stretch goals to try out other parts of Lucene to optimize (e.g.
spatial search).
> Explore
people to use Lucene with CUDA. Lucene has
many extension points already. Though I could imagine you might unfortunately
need to copy/fork some long source files -- Uwe mentioned some.
Good luck.
> Explore GPU acceleration
>
>
> Key:
reading about GPU acceleration and in particular to be
precise about GPU accelerated computing I find this project very interesting
and so can anyone give me further lead what is to be done now? I mean the ideas
that Ishaan suggested are pretty good but I am still not able to understand
that what
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]
vikash commented on LUCENE-7745:
Hi all, I have been reading about GPU acceleration and in particular
e in C code if I would
solely focus on GPU parallelization. The current iterator based approaches are
not easy to transform or plug into CUDA...
For the GSoc project, we should make sure to the GSoc student that this is just
a project to "explore" GPU acceleration: if it brings
on. The current iterator based approaches are
not easy to transform or plug into CUDA...
For the GSoc project, we should make sure to the GSoc student that this is just
a project to "explore" GPU acceleration: if it brings any performance - I doubt
that, because the call overhe
using a GPU, it
would not be, *for the end-user*, the end of the world if the code comes
outside Apache distribution.
bq. If (a) is a "no", we need to be honest up front with the contributor.
That is a good point, and we can document this clearly.
> Explore GPU
. BooleanScorer does with disjunction
of high frequency terms, would be amenable to GPU acceleration? Today
BooleanScorer processes a whole window of hits at once, doing fairly simple
math (the Similarity methods) on each.
> Explore GPU acceleration
>
>
>
? 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
in some areas (esp.
aggregations over column oriented fields):
https://www.slideshare.net/kaigai/gpgpu-accelerates-postgresql
> Explore GPU acceleration
>
>
> Key: LUCENE-7745
> URL: https://issues.apache.org/jira/bro
parallelization?
> Explore GPU acceleration
>
>
> Key: LUCENE-7745
> URL: https://issues.apache.org/jira/browse/LUCENE-7745
> Project: Lucene - Core
> Issue Type: Improvement
>Report
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]
vikash commented on LUCENE-7745:
Hi I am willing to work on this.
> Explore GPU accelerat
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Ishan Chattopadhyaya updated LUCENE-7745:
-
Labels: gsoc2017 mentor (was: )
> Explore GPU accelerat
Ishan Chattopadhyaya created LUCENE-7745:
Summary: Explore GPU acceleration
Key: LUCENE-7745
URL: https://issues.apache.org/jira/browse/LUCENE-7745
Project: Lucene - Core
Issue Type
, Simon Willnauer wrote:
On Sat, Mar 12, 2011 at 9:21 PM, Ken O'Brienk...@kenobrien.org wrote:
Hi,
Is anyone looking at GPU acceleration for Solr? If not, I'd like to
contribute code which adds this functionality.
As I'm not familiar with the codebase, does anyone know which areas
, 2011 at 9:21 PM, Ken O'Brienk...@kenobrien.org wrote:
Hi,
Is anyone looking at GPU acceleration for Solr? If not, I'd like to
contribute code which adds this functionality.
As I'm not familiar with the codebase, does anyone know which areas of
functionality could benefit from high
made the approach unfeasible.
I'll basically replicate existing functionality to run on the gpu.
On 12/03/11 21:08, Simon Willnauer wrote:
On Sat, Mar 12, 2011 at 9:21 PM, Ken O'Brienk...@kenobrien.org wrote:
Hi,
Is anyone looking at GPU acceleration for Solr? If not, I'd like
, Simon Willnauer wrote:
On Sat, Mar 12, 2011 at 9:21 PM, Ken O'Brienk...@kenobrien.org
wrote:
Hi,
Is anyone looking at GPU acceleration for Solr? If not, I'd like to
contribute code which adds this functionality.
As I'm not familiar with the codebase, does anyone know which areas
Hi,
Is anyone looking at GPU acceleration for Solr? If not, I'd like to
contribute code which adds this functionality.
As I'm not familiar with the codebase, does anyone know which areas of
functionality could benefit from high degrees of parallelism.
Regards,
Ken
On Sat, Mar 12, 2011 at 9:21 PM, Ken O'Brien k...@kenobrien.org wrote:
Hi,
Is anyone looking at GPU acceleration for Solr? If not, I'd like to
contribute code which adds this functionality.
As I'm not familiar with the codebase, does anyone know which areas of
functionality could benefit
with that.
I'll basically replicate existing functionality to run on the gpu.
On 12/03/11 21:08, Simon Willnauer wrote:
On Sat, Mar 12, 2011 at 9:21 PM, Ken O'Brienk...@kenobrien.org wrote:
Hi,
Is anyone looking at GPU acceleration for Solr? If not, I'd like to
contribute code which adds this functionality
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