Scheduling Delta-Critical Tasks in Mixed-Parallel Applications on a National Grid

International audienceMixed-parallel applications can take advantage of large-scale computing platforms but scheduling them efficiently on such platforms is challenging. When relying on classic list scheduling algorithms, the issue of independent and selfish task allocation determination may arise. Indeed the allocation of the most critical task may lead to poor allocations for subsequent tasks. In this paper we propose a new mixed-parallel scheduling heuristic that takes into account that several tasks may have almost the same level of criticality during the allocation process. We then perform a comparison of this heuristic with other algorithms in simulation over a wide range of application and on platform conditions. We find that our heuristic achieves better performance in terms of schedule length, speedup and degradation from best

Checkpointing Strategies for Scheduling Computational Workflows

International audienceWe study the scheduling of computational workflows on compute resources that experience exponentially distributed failures. When a failure occurs, rollback and recovery is used to resume the execution from the last checkpointed state. The scheduling problem is to minimize the expected execution time by deciding in which order to execute the tasks in the workflow and deciding for each task whether to checkpoint it or not after it completes. We give a polynomial-time optimal algorithm for fork DAGs (Directed Acyclic Graphs) and show that the problem is NP-complete with join DAGs. We also investigate the complexity of the simple case in which no task is checkpointed. Our main result is a polynomial-time algorithm to compute the expected execution time of a workflow, with a given task execution order and specified to-be-checkpointed tasks. Using this algorithm as a basis, we propose several heuristics for solving the scheduling problem. We evaluate these heuristics for representative workflow configurations