
Parallel programming has become mandatory to fully exploit the potential of multi-core CPUs. The dataflow model provides a natural way to exploit parallelism. However, specifying dependences and control using fine-grained instructions in dataflow programs can be complex and present unwanted overheads. To address this issue, we have designed TALM: a coarse-grained dataflow execution model to be used on top of widespread architectures. We implemented TALM as the Trebuchet virtual machine for multi-cores. The programmer identifies code blocks that can run in parallel and connects them to form a dataflow graph, which allows one to have the benefits of parallel dataflow execution in a Von Neumann machine, with small programming effort. We parallelised a set of seven applications using our approach and compared with OpenMP implementations. Results show that Trebuchet can be competitive with state-of-the-art technology, while providing the benefits of dataflow execution.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 24 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
