Autor: |
Asada, Yuki, Fu, Victor, Gandhi, Apurva, Gemawat, Advitya, Zhang, Lihao, He, Dong, Gupta, Vivek, Nosakhare, Ehi, Banda, Dalitso, Sen, Rathijit, Interlandi, Matteo |
Rok vydání: |
2022 |
Předmět: |
|
Zdroj: |
Proceedings of the VLDB Endowment. 15:3598-3601 |
ISSN: |
2150-8097 |
Popis: |
We demonstrate Tensor Query Processor (TQP): a query processor that automatically compiles relational operators into tensor programs. By leveraging tensor runtimes such as PyTorch, TQP is able to: (1) integrate with ML tools (e.g., Pandas for data ingestion, Tensorboard for visualization); (2) target different hardware (e.g., CPU, GPU) and software (e.g., browser) backends; and (3) end-to-end accelerate queries containing both relational and ML operators. TQP is generic enough to supports the TPC-H benchmark, and it provides performance that are comparable to, and often better than, that of specialized CPU and GPU query processors. |
Databáze: |
OpenAIRE |
Externí odkaz: |
|