Low-Cost Tuning of Two-Step Algorithms for Scheduling Mixed-Parallel Applications onto Homogeneous Clusters

Due to the strong increase of processing units available to the end user, expressing parallelism of an algorithm is a major challenge for many researchers. Parallel applications are often expressed using a task-parallel model (task graphs), in which tasks can be executed concurrently unless they share a dependency. If these tasks can also be executed in a dataparallel fashion, e.g., by using MPI or OpenMP, then we call it a mixed-parallel programming model. Mixed-parallel applications are often modeled as directed acyclic graphs (DAGs), where nodes represent the tasks and edges represent data dependencies. To execute a mixed-parallel application efficiently, a good scheduling strategy is required to map the tasks to the available processors. Several algorithms for the scheduling of mixed-parallel applications onto a homogeneous cluster have been proposed. MCPA (Modified CPA) has been shown to lead to efficient schedules. In the allocation phase, MCPA considers the total number of proce...

• Type: Journal
• Year: 2010
• Where: CCGRID
• Authors: Sascha Hunold
• Keywords: CCGRID 2010, Distributed And Parallel Computing, Mixed-parallel Applications, Mixed-parallel Programming Model, Processors