AwkwardForth: accelerating Uproot with an internal DSL
- 1. Princeton University, Princeton, New Jersey (United States)
- 2. Institute of Engineering and Management, Kolkata, West Bengal (India)
Description
File formats for generic data structures, such as ROOT, Avro, and Parquet, pose a problem for deserialization: it must be fast, but its code depends on the type of the data structure, not known at compile-time. Just-in-time compilation can satisfy both constraints, but we propose a more portable solution: specialized virtual machines. AwkwardForth is a Forth-driven virtual machine for deserializing data into Awkward Arrays. As a language, it is not intended for humans to write, but it loosens the coupling between Uproot and Awkward Array. AwkwardForth programs for deserializing record-oriented formats (ROOT and Avro) are about as fast as C++ ROOT and 10–80× faster than fastavro. Columnar formats (simple TTrees, RNTuple, and Parquet) only require specialization to interpret metadata and are therefore faster with precompiled code.
Availability note (English)
Available from https://www.epj-conferences.org/articles/epjconf/pdf/2021/05/epjconf_chep2021_03002.pdf; https://doaj.org/article/f6557b42090f449084eae9cef42177afAdditional details
Identifiers
Publishing Information
- Journal Title
- EPJ. Web of Conferences
- Journal Volume
- 251
- Journal Page Range
- vp.
- ISSN
- 2100-014X
Conference
- Title
- 25. International Conference on Computing in High Energy and Nuclear Physics
- Acronym
- CHEP 2021
- Dates
- 17-21 May 2021
- Place
- Geneva (Switzerland)
INIS
- Country of Publication
- France
- Country of Input or Organization
- France
- INIS RN
- 53090138
- Subject category
- S97: MATHEMATICAL METHODS AND COMPUTING;
- Resource subtype / Literary indicator
- Conference
- Descriptors DEI
- COMPUTERIZED SIMULATION; DATA ANALYSIS; PROGRAMMING LANGUAGES
- Descriptors DEC
- DATA PROCESSING; PROCESSING; SIMULATION