No abstract

Maintaining memory access locality is continuing to be a challenge for parallel applications and their runtime environments. By exploiting locality, application performance, resource usage, and performance portability can be improved. The main challenge is to detect and fix memory locality issues for applications that use shared-memory programming models for intra-node parallelization. In this paper, we investigate improving memory access locality of a hybrid MPI+OpenMP application in two different ways, by manually fixing locality issues in its source code and by employing the Adaptive MPI (AMPI) runtime environment. Results show that AMPI can result in similar locality improvements as manual source code changes, leading to substantial performance and scalability gains compared to the unoptimized version and to a pure MPI runtime. Compared to the hybrid MPI+OpenMP baseline, our optimizations improved performance by 1.8x on a single cluster node, and by 1.4x on 32 nodes, with a speedup of 2.4x compared to a pure MPI execution on 32 nodes. In addition to performance, we also evaluate the impact of memory locality on the load balance within a node. CCS CONCEPTS • Computer systems organization → Multicore architectures; Distributed architectures; • Software and its engineering → Main memory; Runtime environments;

No abstract

No abstract

The recent trend of rapid increase in the number of cores per chip has resulted in vast amounts of on-node parallelism. These high core counts result in hardware variability that introduces imbalance. Applications are also becoming more complex themselves, resulting in dynamic load imbalance. Load imbalance of any kind can result in loss of performance and decrease in system utilization. In this paper, we propose a new integrated runtime system that adds OpenMP shared-memory parallelism to the Charm++ distributed programming model to improve load balancing on distributed systems. Our proposal utilizes an infrequent periodic assignment of work to cores based on load measurement, in combination with tasks created via OpenMP's parallel loop construct from each core to handle load imbalance. We demonstrate the benefits of using this integrated runtime system on the LLNL ASC proxy application Lassen, achieving speedups of 50% over runs without any load balancing and 10% over existing distributed-memory-only balancing schemes in Charm++. CCS CONCEPTS • Computer systems organization → Multicore architectures; Distributed architectures; • Software and its engineering → Runtime environments;