Power-Aware MPI Task Aggregation Prediction for High-End Computing Systems
Emerging large-scale systems have many nodes with several processors per node and multiple cores per processor. These systems require effective task distribution between cores, processors and nodes to achieve high levels of performance and utilization. Current scheduling strategies distribute tasks between cores according to a count of available cores, but ignore the execution time and energy implications of task aggregation (i.e., grouping multiple tasks within the same node or the same multi-core processor). Task aggregation can save significant energy while sustaining or even improving performance.