LLB: A fast and effective scheduling algorithm for distributed-memory systems

This paper presents a new algorithm called List-based Load Balancing (LLB) for compile-time task scheduling on distributed-memory machines. LLB is intended as a cluster-mapping and task-ordering step in the multi-step class of scheduling algorithms. Unlike current multistep approaches, LLB integrates cluster-mapping and task-ordering in a single step. The benefits of this integration are twofold. First, it allows dynamic load balancing in time, because only the ready tasks are considered in the mapping process. Second, communication is also considered, as opposed to algorithms like WCM and GLB. The algorithm has a low time complexity of O(E+V(log V+log P)), where E is the number of dependences, V is the number of tasks and P is the number of processors. Experimental results show that LLB outperforms known cluster-mapping algorithms of comparable complexity, improving the schedule lengths up to 42%. Furthermore, compared with LCA, a much higher-complexity algorithm, LLB obtains comparable results for fine-grain graphs and yields improvements up to 16% for coarse-grain graphs.