16 citations · 63 across the 8 of their papers we have counts for
7 papers · 1 filter
The Tensor Data Platform: Towards an AI-centric Database System
Apurva Gandhi, Yuki Asada, Victor Fu +6
Database engines have historically absorbed many of the innovations in data processing, adding features to process graph data, XML, object oriented, and text among many others. In…
Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem
Yuki Asada, Victor Fu, Apurva Gandhi +8
We demonstrate Tensor Query Processor (TQP): a query processor that automatically compiles relational operators into tensor programs. By leveraging tensor runtimes such as PyTorch,…
Optimal Resource Allocation for Serverless Queries
Anish Pimpley, Shuo Li, Anubha Srivastava +7
Optimizing resource allocation for analytical workloads is vital for reducing costs of cloud-data services. At the same time, it is incredibly hard for users to allocate resources…
A Comparative Exploration of ML Techniques for Tuning Query Degree of Parallelism
Zhiwei Fan, Rathijit Sen, Paraschos Koutris +1
There is a large body of recent work applying machine learning (ML) techniques to query optimization and query performance prediction in relational database management systems (RDB…
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…