Parallel tree building on a range of shared address space multiprocessors: algorithms and application performance

Irregular, particle-based applications that use trees, for example hierarchical N-body applications, are important consumers of multiprocessor cycles, and are argued to benefit greatly in programming ease from a coherent shared address space programming model. As more and more supercomputing platforms that can support different programming models become available to users, from tightly-coupled hardware-coherent machines to clusters of workstations or SMPs, to truly deliver on its ease of programming advantages to application users it is important that the shared address space model not only perform and scale well in the tightly-coupled case but also port well in performance across the range of platforms (as the message passing model can). For tree-based N-body applications, this is currently not true: while the actual computation of interactions ports well, the parallel tree building phase can become a severe bottleneck on coherent shared address space platforms, in particular on platforms with less aggressive, commodity-oriented communication architectures (even though it takes less 3 percent of the time in most sequential executions). The authors therefore investigate the performance of five parallel tree building methods in the context of a complete galaxy simulation on four very different platforms that support this programming model