Evaluating End-to-End Optimization for Data Analytics Applications in Weld. S. Palkar et al. PVLDB 2018

Taro L. Saito
Jul 13, 2018 · 1 min read
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Weld is an approach to optimize the whole program by using a common intermediate representation (IR) for Spark SQL, TensorFlow, Python Pandas, NumPy, etc. IRs generated from various libraries will be combined together to optimize the entire code as a whole. This PVLDB paper is a follow-up work of the initial paper published at CIDR 2017, and it presents the efficiency of rule-based optimizations, such as code fusion between libraries, loop-unrolling, vectorization, etc. Weld generates multi-threaded LLVM code from an optimized IR, and the experimental results show comparable performance with specialized data processing engine like HyPer (VLDB 2011), which also generates LLVM code from SQL.

Database Journal Club

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Taro L. Saito

Written by

Ph.D., researcher and software engineer, pursuing database technologies for everyone http://xerial.org/leo

Database Journal Club

Database Journal Club is a public community for exploring database research field through published journals and research papers.

Taro L. Saito

Written by

Ph.D., researcher and software engineer, pursuing database technologies for everyone http://xerial.org/leo

Database Journal Club

Database Journal Club is a public community for exploring database research field through published journals and research papers.

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