Compact DAG Representation and its Dynamic Scheduling

Article dans revue scientifique avec comité de lecture.Scheduling large task graphs is an important issue in parallel computing. In this paper, we tackle the two following problems : (1) how to schedule a task graph, when it is too large to fit into memory, (2) how to build a generic program such that parameter values of a task graph can be given at run-time. Our answer features the parameterized task graph (PTG) which is a symbolic representation of the task graph. We propose a dynamic scheduling algorithm which takes a PTG as an entry and allows to generate a generic program. We present a theoritical study which shows that our algorithms find good schedules for coarse grain task graphs, has a very low memory cost and a low computational complaxity. When the average number of operations of each task is large enough, we prove that the scheduling overhead is negligible with respect to the makespan. We also provide experimental results that demonstrate the feasibility of our approach using several compute-intensive kernels found in numeric scientific applications