Discover how modern Java features, including vectorization and FFI/madvise, are speeding up Lucene's performance.

Foreign memory

Foreign function

Vectorization

Conclusion

Lucene & Java: How vectorization & FFI/madvise speed up Lucene

Making Lucene faster with vectorization and FFI/madvise

How we optimized vector comparisons in BBQ with hardware accelerated SIMD (Single Instruction Multiple Data) instructions.

Why do we care so much about comparing vectors?

Comparing query and stored vectors

Where does the performance come from?

How much does SIMD improve things?

Wrapping up

BBQ: Optimizing vector comparisons with hardware accelerated SIMD instructions

Smokin' fast BBQ with hardware accelerated SIMD instructions

Learn how to use fused multiply-add (FMA) within vector similarity computations in Lucene and discover how FMA can improve performance.

What is fused multiply-add (FMA)

FMA in Lucene: Under the hood

Performance improvements with FMA

Fused multiply-add (FMA) is a single operation that performs both the multiply and add operations in one - the multiplication and addition are said to be “fused” together. FMA is typically faster than a separate multiplication and addition and produces more accurate results.

What is fused multiply-add (FMA)?

Understanding fused multiply add (FMA) in Lucene

Understanding fused multiply-add (FMA) within vector similarity computations in Lucene

Learn how to optimize vector distance computations using the Foreign Function & Memory (FFM) API to achieve faster performance.

Current state of play: The Panama Vector API

Introducing the Foreign Function & Memory (FFM) API

FFM usage example

Going foreign

Back in Java-land

Performance improvements with FFM API

Summary

Optimizing vector distance computations with the FFM API

Optimizing vector distance computations with the Foreign Function & Memory (FFM) API

Author

Chris Hegarty

Articles

Making Lucene faster with vectorization and FFI/madvise

Smokin' fast BBQ with hardware accelerated SIMD instructions

Understanding fused multiply-add (FMA) within vector similarity computations in Lucene

Optimizing vector distance computations with the Foreign Function & Memory (FFM) API