Local and Global Shared Memory for Task Based HPC Applications on Heterogeneous Platforms

Abstract

With the prevalence of multicore and manycore processors, developing parallel applications to bene?t from massively parallel resources is important. In this work, we introduce a hybrid shared memory mechanism based on a high-level task design. We implemented task scoped global shared data based on the one-sided communication feature of MPI-3 and enable users to implement and create multi-threaded tasks that can execute either on a single node or on multiple nodes. Task threads of distributed nodes can share data sets through global shared data objects using one-sided remote memory access. We ported and developed a set of benchmark applications and tested on a cluster platform. The high-level task design and hybrid shared memory help users develop and maintain parallel programs easily, and the results show that the global shared data can deliver good RMA performance; the multi-threaded task implementations perform up to 20% faster than ordinary OpenMP programs and have better scaling performance than MPI programs on multiple nodes.