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A Delegation Mechanism on Many-Core Oriented Hybrid Parallel Computers for Scalability of Communicators and Communications in MPI

机译:用于多核导向混合并行计算机的委派机制,用于MPI中的通信者和通信的可扩展性

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This paper describes a delegation based high throughput MPIcommunication mechanism under tough memory utilization constrains on a many-core oriented hybrid parallel computer. Towards the Exascale era, hybrid parallel computers consisting of many-core and multi-core architectures both on the same node are focused. Although many-core architectures such as GPU or Intel MIC has high potential in computing power by the large number of computing cores, per-core computing power is lower than that of multi-core CPUs. Furthermore, available memory resources for the many-core CPUs are quite smaller than those for multi-core CPUs. Thus we may have a sort of penalty in memory utilization in MPI communications when we utilize a normal MPI library. Here we deploy a delegatee process on each node to merge MPI communications and minimize memory utilization for an MPI communicator. Another advantage of the delegatee process scheme is minimization of memory utilization on many-core CPUs by delegating MPI requests to associated delegatee process on multi-core CPUs. In this paper, we show performance advantages and effective resource utilization by our proposed scheme compared with the original MPI implementation.
机译:本文介绍了基于委托的高吞吐量MPIConmunication机制,在很多核心定向的混合并行计算机上的严重内存利用率下约束。朝向ExaScale时代,聚集在同一节点上的许多核心和多核架构组成的混合并行计算机。尽管通过大量计算核心,但GPU或Intel MIC等许多核心架构在计算功率上具有很高的计算机,但每核计算功率低于多核CPU的计算能力。此外,许多核心CPU的可用内存资源非常小于多核CPU的内存资源。因此,当我们利用普通MPI库时,我们可能在MPI通信中具有一种处于内存利用率的惩罚。在这里,我们在每个节点上部署抄级过程以合并MPI通信并最大限度地减少MPI通信器的内存利用率。 DELEGATEE Process Scheme的另一个优点是通过将MPI请求委派到多核CPU上的相关代表人进程来最小化许多核心CPU上的内存利用率。在本文中,与原始MPI实施相比,我们通过拟议方案显示性能优势和有效资源利用。

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