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Online Scheduling of Applications on 3D Stacked Large Chip Multiprocessor

机译:3D堆叠大型芯片多处理器上应用程序的在线计划

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Performance of 3D stacked memory is impressive in multicore system. In three dimensional stacked large chip multiprocessor (3D LCMP), memory and memory network are integrated on top of the processors and processor network. In this paper, we have proposed an online strategy for mapping application's tasks and data onto 3D LCMP platforms. To meet performance constraints every application demand a set of resources (may be number of processor and amount of memory). An important criteria in allocation is to allocate all required resources as near as possible to reduce the communication overhead. We have proposed approximate nearest approach to allocate resources of a layer with respect to other resource layer (either processor or memory). In our work, we have compared three different strategies to allocate resources to application: in first one processor allocation is preferred over memory allocation, in second one memory allocation is preferred over processor and in third one priority is set depend on requirement of applications. Our experimental analysis shows 21% in average and up to 30% improvement over state of art one layer resource allocation. On demand priority based resource allocation improve 26% over simple processor or memory priority based resource allocation.
机译:3D堆栈存储器的性能在多核系统中令人印象深刻。在三维堆叠的大型芯片多处理器(3D LCMP)中,内存和内存网络集成在处理器和处理器网络的顶部。在本文中,我们提出了一种在线策略,用于将应用程序的任务和数据映射到3D LCMP平台上。为了满足性能限制,每个应用程序都需要一组资源(可能是处理器数量和内存量)。分配中的重要标准是尽可能地分配所有必需的资源,以减少通信开销。我们提出了一种近似最近的方法来相对于其他资源层(处理器或内存)分配一个层的资源。在我们的工作中,我们比较了三种为应用程序分配资源的策略:第一种方法是分配内存,而不是分配内存;第二种方法,分配内存是,而不是处理器;第三种,根据应用程序的要求来设置优先级。我们的实验分析显示,平均水平比最先进的一层资源分配高21%,最多可提高30%。基于请求的优先级的资源分配比基于简单处理器或内存优先级的资源分配提高了26%。

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