TreeToaster: Towards an IVM-Optimized Compiler
Darshana Balakrishnan, Carl Nuessle, Oliver Kennedy, Lukasz Ziarek
摘要
A compiler's optimizer operates over abstract syntax trees (ASTs), continuously applying rewrite rules to replace subtrees of the AST with more efficient ones. Especially on large source repositories, even simply finding opportunities for a rewrite can be expensive, as optimizer traverses the AST naively. In this paper, we leverage the need to repeatedly find rewrites, and explore options for making the search faster through indexing and incremental view maintenance (IVM). Concretely, we consider bolt-on approaches that make use of embedded IVM systems like DBToaster, as well as two new approaches: Label-indexing and TreeToaster, an AST-specialized form of IVM. We integrate these approaches into an existing just-in-time data structure compiler and show experimentally that TreeToaster can significantly improve performance with minimal memory overheads.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper1
问问它们各自怎么用它相关 Paper
- Efficient Incrementialization of Correlated Nested Aggregate Queries using Relative Partial Aggregate Indexes (RPAI)Supun Abeysinghe, Qiyang He, Tiark RompfSIGMOD 2022 · 被引用 7 次
- An efficient interpreter for Datalog by de-specializing relationsXiaowen Hu, David Zhao, Herbert Jordan, Bernhard ScholzPLDI 2021 · 被引用 6 次
- Adaptive Code Generation for Data-Intensive AnalyticsWangda Zhang, Junyoung Kim, Kenneth A. Ross, Eric Sedlar 等VLDB 2021 · 被引用 12 次
- Treebeard: An Optimizing Compiler for Decision Tree Based ML InferenceAshwin Prasad, Sampath Rajendra, Kaushik Rajan, R. Govindarajan 等MICRO 2022 · 被引用 8 次
- Benchmarking the Full Pipeline of Materialized-View-Based Query RewritingXinjie Hu, Zhengjie MiaoVLDB 2026
