1 citations · 1 across the 5 of their papers we have counts for
6 papers
VADER: Filtered Vector Search with Declarative Recall
Manos Chatzakis, Duo Lu, Helena Caminal +7
Approximate filtered vector search (FVS), a core operation in many data management tasks that combine structured data with vector embeddings, exhibits increased complexity due to t…
Over the Memory Wall, Into the Instruction Wall: The New Bottleneck in GPU Data Processing
Sven Hepkema, Bowen Wu, Christos Kozyrakis +2
Datacenter GPUs have seen an order-of-magnitude increase in memory bandwidth with the adoption of newer generations of HBM. Meanwhile, GPU database systems are gaining traction, ma…
To GPU or Not to GPU: Vector Search in Relational Engines
Vasilis Mageirakos, Joel André, Marko Kabić +3
Vector search (VS) is now available in most database engines. However, while vector search is a common feature in AI/ML/LLMs where the dominant computing platforms are GPUs, existi…
An In-Depth Study of Filter-Agnostic Vector Search on a PostgreSQL Database System: [Experiments and Analysis]
Duo Lu, Helena Caminal, Manos Chatzakis +4
Filtered Vector Search (FVS) is critical for supporting semantic search and GenAI applications in modern database systems. However, existing research most often evaluates algorithm…
Is it Bigger than a Breadbox: Efficient Cardinality Estimation for Real World Workloads
Zixuan Yi, Sami Abu-el-Haija, Yawen Wang +8
DB engines produce efficient query execution plans by relying on cost models. Practical implementations estimate cardinality of queries using heuristics, with magic numbers tuned t…
CardBench: A Benchmark for Learned Cardinality Estimation in Relational Databases
Yannis Chronis, Yawen Wang, Yu Gan +4
Cardinality estimation is crucial for enabling high query performance in relational databases. Recently learned cardinality estimation models have been proposed to improve accuracy…