首页> 外文期刊>Procedia Computer Science >Scaling Score-P to the next level * * This material is based upon work supported by the US Department of Energy under Grant No. DE-SC0015524 and by the German Federal Ministry for Education and Research (BMBF) under Grant No. 01IH13001.
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Scaling Score-P to the next level * * This material is based upon work supported by the US Department of Energy under Grant No. DE-SC0015524 and by the German Federal Ministry for Education and Research (BMBF) under Grant No. 01IH13001.

机译:将Score-P扩展到下一个级别 * * 此材料基于美国能源部根据拨款号支持的工作。DE-SC0015524以及德国联邦教育与研究部(BMBF)的授权号01IH13001。

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As part of performance measurements with Score-P, a description of the system and the execution locations is recorded into the performance measurement reports. For large-scale measurements using a million or more processes, the global system description can consume all the available memory. While the information stored process-locally during measurement is small, the memory requirement becomes a bottleneck in the process of constructing a global representation of the whole system. To address this problem we implemented a new system description in Score-P that exploits regular structures of the system, and results, on homogeneous systems, in a system description of constant size. Furthermore, we present a parallel algorithm to create a global view from the process-local information. The scalable system description comes at the price that it is no longer possible to assign individual names to each system element, but only enumerate elements of the same type. We have successfully tested the new approach on the full JUQUEEN system with up to nearly two million processes.
机译:作为使用Score-P进行绩效评估的一部分,系统和执行位置的描述会记录在绩效评估报告中。对于使用一百万或更多进程的大规模测量,全局系统描述会占用所有可用内存。尽管在测量过程中本地存储的信息很小,但是在构建整个系统的全局表示过程中,内存需求成为瓶颈。为了解决这个问题,我们在Score-P中实现了一个新的系统描述,该描述利用了系统的规则结构,并在同类系统上得出了恒定大小的系统描述。此外,我们提出了一种并行算法,用于根据过程本地信息创建全局视图。可伸缩的系统描述的代价是不再可能为每个系统元素分配单独的名称,而只能枚举相同类型的元素。我们已经在多达200万个流程的完整JUQUEEN系统上成功测试了新方法。

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