Re: How about using JDK 21 in the official docker image?

[Shawn Heisey]

On 10/18/2023 10:11 AM, Tomasz Elendt wrote:

I noticed that JDK 21 LTS was released some time ago. Is there any reason why 
official docker images still use JDK 17?

I'm asking because I know there are some preview JDK features that Lucene 
utilizes and Solr enables them when it detects a newer version (e.g. 
SOLR-16500).

Does it make sense to switch now that there is a new LTS version?


I have no desire to stand in the way of progress, but Java 21 has only 
been out for a month.  I don't think it's a good idea to rely on a new 
major version of *anything* that soon after its release.  Test with it, 
but don't switch to it.


I do not think we should be planning on such a major upgrade to the 
docker image until Java 21 has been out for a while.  I was going to 
upgrade my Solr server to Java 21 to try it out since it's not a mission 
critical install, but Ubuntu doesn't yet have OpenJDK packages for it. 
The eclipse-temurin:21-jre-jammy docker image was pushed 11 days ago.


My thought on it is to wait until at least the release of Java 22, which 
will happen six months after Java 21 was released.


Thanks,
Shawn

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Re: RAPIDS RAFT

[Ishan Chattopadhyaya]

+Solr list, Lucene list, FYI

On Wed, 25 Oct, 2023, 9:13 am Ishan Chattopadhyaya, 
wrote:

>
> Hi Nathan,
>
> I am a committer and PMC member of Apache Solr and Apache Lucene. I have
> integrated CUDA into Lucene in the past:
> https://twitter.com/ichattopadhyaya/status/1065136227500867585
>
> I am interested in pursuing this integration for Apache Solr. Would you be
> interested in discussing this further?
>
> Regards,
> Ishan Chattopadhyaya
> Search Consultant, SearchScale
>
>
> On Wed, 25 Oct, 2023, 5:10 am Nathan Stephens,
>  wrote:
>
>> Lucene,
>>
>> I have talked to OpenSearch, Datastax, Elastic, Lucidworks, and Atlas
>> about integrating NVIDIA RAFT for GPU accelerated VSS. They all use Lucene
>> at some level. Rather than integrating into each, we would like to
>> integrate foundationally into Lucene.
>>
>> Could we set up some time and make some introductions?
>>
>> You can read more about RAFT here:
>>
>> Accelerating Vector Search: Using GPU-Powered Indexes with RAPIDS RAFT |
>> NVIDIA Technical Blog
>> 
>>
>> Accelerating Vector Search: Fine-Tuning GPU Index Algorithms | NVIDIA
>> Technical Blog
>> 
>>
>> Thanks,
>>
>> Nathan
>> --
>> *From:* Nathan Stephens 
>> *Sent:* Monday, August 14, 2023 9:32 AM
>> *To:* d...@lucene.apache.org 
>> *Subject:* RAPIDS RAFT
>>
>> NVIDIA has created accelerated vector search algorithms for IVF-Flat,
>> IVF-PQ, and CAGRA (a new graph based algorithm specifically designed for
>> GPU's). These algorithms are part of RAPIDS RAFT.  RAFT contains
>> fundamental widely-used algorithms and primitives for machine learning and
>> information retrieval. The algorithms are CUDA-accelerated and form
>> building blocks for more easily writing high performance applications.
>> API's exist for Python and C++ (we do not currently have a Java API).
>>
>> RAFT has been integrated into Milvus, Redis, and Faiss. We are looking
>> for other integration partners. I wanted to see if there was an interest in
>> the Lucene community.
>>
>> https://github.com/rapidsai/raft
>>
>> Nathan
>>
>>
>>
>> *Nathan Stephens* (He/Him/His)
>> Enterprise Products: Data Science, AI/ML
>>
>> NVIDIA 
>>
>