计算网格中拓扑感知集体操作的多层方法
A Multilevel Approach to Topology-Aware Collective Operations in Computational Grids
摘要：
如何有效地实施集体通信业务受到了广泛的关注。最初的努力产生了基于网络通信模型的“最优”树，该模型假设任何两个进程之间的点对点延迟相等。然而，这种假设在大多数实际环境中是违反的，特别是在异构系统中，如SMP集群和广域“计算网格”，结果是集体操作执行次优。作为响应，最近的工作集中在为集体操作创建拓扑感知树，该集体操作最小化跨较慢通道的通信（例如，广域网）。虽然这些努力具有显著的通信优势，但它们都将网络的视图限制在两层。我们提出了一种基于网络的多层视图的策略。通过创建多级拓扑感知树，我们利用了网络中每一级的通信成本差异。我们使用此策略在MPICH-G2中实现了几个MPI集体操作的拓扑感知版本，MPICH-G2是MPI标准的流行MPICH实现的Globus Toolkit[tm]启用版本。利用MPICH-G2提供的拓扑信息，我们在执行过程中自动构建这些多级拓扑感知树。我们目前的结果表明，我们的多级方法的优势，通过比较它的默认（拓扑不知道）的MPICH和拓扑感知的两层实现提供的实现。
英文摘要：
The efficient implementation of collective communiction operations has received much attention. Initial efforts produced "optimal" trees based on network communication models that assumed equal point-to-point latencies between any two processes. This assumption is violated in most practical settings, however, particularly in heterogeneous systems such as clusters of SMPs and wide-area "computational Grids," with the result that collective operations perform suboptimally. In response, more recent work has focused on creating topology-aware trees for collective operations that minimize communication across slower channels (e.g., a wide-area network). While these efforts have significant communication benefits, they all limit their view of the network to only two layers. We present a strategy based upon a multilayer view of the network. By creating multilevel topology-aware trees we take advantage of communication cost differences at every level in the network. We used this strategy to implement topology-aware versions of several MPI collective operations in MPICH-G2, the Globus Toolkit[tm]-enabled version of the popular MPICH implementation of the MPI standard. Using information about topology provided by MPICH-G2, we construct these multilevel topology-aware trees automatically during execution. We present results demonstrating the advantages of our multilevel approach by comparing it to the default (topology-unaware) implementation provided by MPICH and a topology-aware two-layer implementation.
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