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Dryad: distributed data-parallel programs from sequential building blocks
Abstract
Dryad is a general-purpose distributed execution engine for coarse-grain data-parallel applications. A Dryad application combines computational "vertices" with communication "channels" to form a dataflow graph. Dryad runs the application by executing the vertices of this graph on a set of available computers, communicating as appropriate through flies, TCP pipes, and shared-memory FIFOs.
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Cited by
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Data-intensive applications, challenges, techniques and technologies: A survey on Big Data
Philip Chen, C. L., & Zhang, C.-Y. (2014) · Information Sciences · doi:10.1016/j.ins.2014.01.015 · Cited by 3,047
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Apache Spark: A unified engine for big data processing
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Metadata
- Authors
- Isard, M., Budiu, M., Yu, Y., Birrell, A., & Fetterly, D.
- Venue
- Proceedings of the 2nd ACM SIGOPS/EuroSys European Conference on Computer Systems 2007
- Publisher
- ACM
- Published
- 2007-03-21
- Pages
- 59-72
- OpenAlex
- W2100830825
- Cited by
- 2,432
- References
- 0
- FWCI
- 81.23
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Dryad: distributed data-parallel programs from sequential building blocks. https://app.cochat.ai/papers/10.1145/1272996.1273005
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- Isard, M., Budiu, M., Yu, Y., Birrell, A., & Fetterly, D. (2007). Dryad: distributed data-parallel programs from sequential building blocks. Proceedings of the 2nd ACM SIGOPS/EuroSys European Conference on Computer Systems 2007. https://doi.org/10.1145/1272996.1273005
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
