53 citations · 152 across the 7 of their papers we have counts for
8 papers · 1 filter
Exqutor: Extended Query Optimizer for Vector-augmented Analytical Queries
Hyunjoon Kim, Chaerim Lim, Hyeonjun An +2
Vector similarity search is becoming increasingly important for data science pipelines, particularly in Retrieval-Augmented Generation (RAG), where it enhances large language model…
VIP Hashing -- Adapting to Skew in Popularity of Data on the Fly (extended version)
Aarati Kakaraparthy, Jignesh M. Patel, Brian P. Kroth +1
All data is not equally popular. Often, some portion of data is more frequently accessed than the rest, which causes a skew in popularity of the data items. Adapting to this skew c…
End-to-end Optimization of Machine Learning Prediction Queries
Kwanghyun Park, Karla Saur, Dalitso Banda +3
Prediction queries are widely used across industries to perform advanced analytics and draw insights from data. They include a data processing part (e.g., for joining, filtering, c…
Query Processing on Tensor Computation Runtimes
Dong He, Supun Nakandala, Dalitso Banda +7
The huge demand for computation in artificial intelligence (AI) is driving unparalleled investments in hardware and software systems for AI. This leads to an explosion in the numbe…
Lessons learned from the early performance evaluation of Intel Optane DC Persistent Memory in DBMS
Yinjun Wu, Kwanghyun Park, Rathijit Sen +2
Non-volatile memory (NVM) is an emerging technology, which has the persistence characteristics of large capacity storage devices(e.g., HDDs and SSDs), while providing the low acces…
Extending Relational Query Processing with ML Inference
Konstantinos Karanasos, Matteo Interlandi, Doris Xin +10
The broadening adoption of machine learning in the enterprise is increasing the pressure for strict governance and cost-effective performance, in particular for the common and cons…
Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML
Ashvin Agrawal, Rony Chatterjee, Carlo Curino +19
Machine learning (ML) has proven itself in high-value web applications such as search ranking and is emerging as a powerful tool in a much broader range of enterprise scenarios inc…
Optimization of Imperative Programs in a Relational Database
Karthik Ramachandra, Kwanghyun Park, K. Venkatesh Emani +3
For decades, RDBMSs have supported declarative SQL as well as imperative functions and procedures as ways for users to express data processing tasks. While the evaluation of declar…