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Many concurrent programs require some form of conditional synchronization to coordinate the execution of different program
tasks. Programming these algorithms using transactional memory (TM) often results in a high conflict rate between transactions. In
this paper we propose an Atomic dataflow model - ADF, which aims to reduce transaction conflicts by incorporating dataflow
scheduling principles into transactional memory. The ADF model is based on the execution of atomic units of work called ADF
tasks. A programmer explicitly defines data dependencies for the ADF task using the trigger set extension. Trigger set data is
implicitly tracked by the TM runtime system, which detects changes and enables the re-execution of a transaction when its
dependencies are satisfied. In this paper we fully describe the ADF model, present its syntax and show advantages of the model
on a practical example.
CitationGajinov, V. [et al.]. Integrating dataflow abstractions into transactional memory. A: Workshop on Systems for Future Multi-Core Architectures. "First Workshop on Systems for Future Multi-Core Architectures". Salzburg: 2011, p. 1-7.
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