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</script>Task-based runtime systems are adopted by application developers for their valuable features including flexibility of execution and optimized resource management. However, the use of such advanced programming models in complex HPC applications often requires significant training time and programming effort. In this work, we share experiences and lessons learned from the use of StarPU in three independent projects of various complexity. We reach conclusions, with respect to training, programming effort, and existing challenges, that are useful to the communities of application developers, as well as to the developers of runtime systems. Finally, we suggest extensions to the runtime systems beneficial to application developers.
task-based programming models, HPC, [INFO.INFO-DC] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], StarPU
task-based programming models, HPC, [INFO.INFO-DC] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], StarPU
| citations 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). | 1 | |
| 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. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 33 | |
| downloads | 9 |

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