Fault Tolerance in Parallel Implementations of Functional Languages
Raj Jagannathan, Edward A. Ashcroft · 2005
Computing models for functional language programs not only facilitate automatic exploitation of inherent parallelism, but they also provide for implicit tolerance to hardware faults through temporal and spatial redundancy. In this paper, we argue that faulttolerance can be achieved more efficiently by using intensional computing models (eduction) rather than extensional computing models (reduction). While intensional computing models can be implemented by using either data-driven execution or demand-driven execution, we show that the latter is naturally suited.