14 citations · 19 across the 6 of their papers we have counts for
4 papers · 1 filter
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…
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…
CodegenBench: Can LLMs Write Efficient Code Across Architectures?
Jie Li, Wenzhao Wu, Junqi Hu +5
While large language models (LLMs) have been extensively evaluated on code generation tasks for general-purpose programming and GPU-accelerated environments (e.g., PyTorch, CUDA),…
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…