3 papers
cs.DB2026
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…
cs.DB2026
Eiger: An Efficient Library for GPU-based Data Analytics
Bowen Wu, Marko Kabić, Sven Hepkema +3
GPUs have become an increasingly attractive platform for accelerating analytical workloads due to their massive parallelism and high memory bandwidth. Recent studies show that in s…
cs.LG2026
A Super Fast K-means for Indexing Vector Embeddings
Leonardo Kuffo, Sven Hepkema, Peter Boncz
We present SuperKMeans: a k-means variant designed for clustering collections of high-dimensional vector embeddings. SuperKMeans' clustering is up to 7x faster than FAISS and Sciki…