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Program implementation based on macro data flow paradigm with RDMA communication support

机译:基于宏数据流范例的程序实现,具有RDMA通信支持

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In this paper, we discuss execution methodology for parallel fine grain programs based on the macro data flow paradigm applied to a FDTD program which is an example of fine grain parallel application based on regular computations executed in an irregular domain. Parallel applications are executed in a MIMD system with message passing implemented with RDMA facility based on rotating buffers control infrastructure. It is shown that such execution model for fine grain parallel applications can facilitate control and synchronization of resources involved in computations and communication. Execution based on macro data flow paradigm reduces synchronization overhead which can not be avoided in message passing communication. This is achieved at a cost of processor time spent on monitoring of program macro node states since we use here a traditional von Neuman system with architectural model unsupported for macro data flow execution. To achieve the best speedup, assignment of macro nodes to physical processors is proceeded by static analysis of program code and optimal decisions as regards node definition/allocation have to be taken.
机译:在本文中,我们基于应用于FDTD程序的宏数据流范例讨论并行细晶粒程的执行方法,其是基于在不规则域中执行的规则计算的细粒并行应用的示例。并行应用程序在MIMD系统中执行,该MIMD系统基于旋转缓冲器控制基础设施与RDMA设施实现的消息传递。结果表明,用于细粒度并行应用的这种执行模型可以促进计算和通信所涉及的资源的控制和同步。基于宏数据流范例的执行减少了在消息传递通信中无法避免的同步开销。这是以处理器时间的成本实现的,因为我们在这里使用具有架构模型的传统von Neuman系统,因此在这里使用了一个传统的von neuman系统,不支持宏数据流执行。为了实现最佳加速度,通过对节点定义/分配的节点定义/分配,通过静态分析进行宏节点对物理处理器的分配。

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