Falkon: a Fast and Light-weight tasK executiON framework
By Ioan Raicu, Yong Zhao, Catalin Dumitrescu, Ian T Foster, M. Wilde. International Conference on Software Composition, 2007
378 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Information Systems, Information Systems and Management
View Paper: https://www.semanticscholar.org/paper/e00b7576829fbd2bda40825d057eefcc5a74c506
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Ioan Raicu
- Yong Zhao
- Ian T Foster
- Shiyong Lu
- M. Wilde
- Tiberiu Stef-Praun
- Veronika Nefedova
- Gregor von Laszewski
In Information Systems
- Yong Zhao
- Ioan Raicu
- Ian T Foster
- Shiyong Lu
- M. Wilde
- Tiberiu Stef-Praun
- Veronika Nefedova
- Gregor von Laszewski
In Information Systems and Management
Citations in the corpus
- Exploiting Dynamic Resource Allocation for Efficient Parallel Data Processing in the Cloud (2011, neutral): “Building upon components like CoG Karajan [26], Falkon [21], and Globus [12], the authors present a scripting language which allows to create mappings between logical and physical data structures and to conveniently assign tasks to these.”
- Remote sensing big data computing: Challenges and opportunities (2015, neutral): “Swift [93] integrates Karajan [93] to provide concise specification and scheduling for task graph, also incorporates Falkon [94] a lightweight execution framework for efficient dispatch of large numbers of tasks in Grids.”
- Cloud Computing and Grid Computing 360-Degree Compared (2008, methodology): “General-purpose components such as GARA (general architecture for advanced reservation) [17], and specialized resource management services such as Falkon [40] (although strictly speaking, Falkon also provides services beyond the fabric layer).”
- Many-task computing for grids and supercomputers (2008, methodology): “3) Keeping data size modest, but increasing the number of tasks moves us into the loosely coupled applications involving many tasks (yellow); Swift/Falkon [6, 7] and Pegasus/DAGMan [8] are examples of this category.”
- Swift: Fast, Reliable, Loosely Coupled Parallel Computation (2007, methodology): “1239 2510 3683 4808 456 866 992 1123 120 327 546 678 0 1000 2000 3000 4000 5000 6000 120 240 360 480 Input Data Size (Volumes) Time (s) GRAM GRAM/Clustering Falkon”