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Releases: tensorchord/VectorChord

0.2.1

19 Feb 13:05
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Major Improvement

We optimize the external centroid index building speed, about 30%. Now it takes about 30h to build index for 100M vectors with only 4 vcpu on i4i.xlarge.

What's Changed

  • refactor: move algorithm to a crate by @usamoi in #172
  • feat: pinning index in memory when building, second try by @usamoi in #181
  • fix: use linked list of vectors to skip realloc by @usamoi in #182
  • feat: use select algorithm to replace heap, if k in top-k is expected to be small by @usamoi in #183
  • ci: install pg13 in docker image by @usamoi in #186
  • ci: use less docker by @usamoi in #187
  • feat: rerank by fetching vectors in heap table by @usamoi in #189
  • ci: enable CI for pg13 by @usamoi in #185
  • chore: update dependencies by @usamoi in #190
  • refactor: remove meaningless target feature requirements by @usamoi in #192
  • fix: test simd operations in emulator by @usamoi in #193
  • feat: neon impl of u8::reduce_sum_of_x by @usamoi in #194
  • chore: update 0.2.1 schema (upgrade) script by @usamoi in #195

Full Changelog: 0.2.0...0.2.1

0.2.0

27 Jan 05:47
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VectorChord 0.2 Release Notes

We are thrilled to announce the release of VectorChord 0.2, advancing vector search capabilities within PostgreSQL.

🚀 New Features

Optimized Storage Layout

  • Long Cross-Page Vector Support: Redesigned internal storage allows vectors to span multiple 8KB PostgreSQL pages, enabling support for vectors with over 2000 dimensions, up to 16000 dim.
  • Enhanced Storage Efficiency: Achieves higher storage density by minimizing wasted space, reducing index size by up to 50% compared to version 0.1.

Additional Data Types

  • Float16 Support: Introduces Float16 data type, allowing users to halve the storage space required with a slight decrease in recall. Note that Float16 does not reduce the size of quantized vectors, maintaining 1 bit per dimension for original vector representation.

Architecture Enhancements

  • ARM Architecture Support: Rewritten distance calculations and Fast Scan implementations using the Scalable Vector Extension (SVE) instruction set for optimal performance on ARM-based systems.
  • AWS Graviton4 Compatibility: Leverage the latest i8g platform based on Graviton4 processors for improved performance at the same cost as i4i models.

⚡ Performance Improvements

  • Reduced Index Size: Up to 50% reduction in index size compared to version 0.1.

🔧 Getting Started

  • Comprehensive getting started guides will be available soon.

📝 Summary

VectorChord 0.2 introduces support for high-dimensional vectors, Float16 data type, ARM architecture optimizations, and a more compact storage layout. These enhancements collectively improve storage efficiency and query performance, providing a superior vector retrieval experience within PostgreSQL.

What's Changed

New Contributors

Full Changelog: 0.1.0...0.2.0

0.1.1-alpha.1

18 Dec 14:32
f88b1ac
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0.1.1-alpha.1 Pre-release
Pre-release

Highlights

  • Support fp16 vec
  • Support vector longer than 2000 dim

What's Changed

New Contributors

Full Changelog: 0.1.0...0.1.1-alpha.1

0.1.0

14 Nov 12:00
db1c2ed
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chore: fix release ci (#85)

Signed-off-by: Keming <[email protected]>