The latest trends in high performance computing systems show an increasing demand on the use of a large scale multicore system in an efficient way so that high compute-intensive applications can be executed reasonably well. However, the exploitation of the degree of parallelism available at each multicore component can be limited by the poor utilization of the memory hierarchy. Actually, the multicore architecture introduces some distinct features that are already observed in shared memory and distributed environments. One example is that subsets of cores can share different subsets of memory. In order to achieve high performance, it is imperative that a careful allocation scheme of an application is carried out on the available cores, based on a scheduling specification that considers not only processors characteristics but also memory contention. This paper proposes a multicore cluster representation that captures relevant performance characteristics in multicores systems such as the influence of memory hierarchy and contention on application performance. Improved performance was achieved by a branch-and-bound application applied to the partitioning sets problem that incorporated a memory aware load balancing strategy based on the proposed multicore cluster representation. An in-depth analysis on this application execution showed its applicability to modern systems. Copyright ©2014 John Wiley & Sons, Ltd.
['Juliana M. N. Silva', 'Cristina Boeres', 'Lúcia Maria de A. Drummond', 'Artur Alves Pessoa']
Memory aware load balance strategy on a parallel branch-and-bound application