PIUMA的降比例模拟性能预测

Stijn Eyerman, W. Heirman, Y. Demir, Kristof Du Bois, I. Hur
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引用次数: 2

摘要

可编程集成统一内存架构(PIUMA)是英特尔的新型图形分析优化处理器架构,目标是在非常大的图形上有效地执行图形算法。在系统建立之前,通过仿真来预测其对各种算法的性能。然而,由于仿真器的仿真速度低、资源占用高、可扩展性差,它们所能模拟的内核和线程数量有限。因此,在整个系统规模下模拟PIUMA实际上是不可能的。在本文中,我们提出了缩小规模的模拟,这是一种利用小规模模拟来预测大规模系统性能的技术。我们将该技术应用于PIUMA,展示了如何配置缩小的系统,以便准确地反映整个系统的特征。我们在一组图形应用程序上评估了缩小规模的模拟,表明它准确地跟踪了小规模模拟的模拟结果,以及由分析模型对大型系统的预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Projecting Performance for PIUMA using Down-Scaled Simulation
Programmable Integrated Unified Memory Architecture (PIUMA) is Intel's novel graph analysis optimized processor architecture, targeted at efficiently executing graph algorithms on very large graphs. Simulation is used to project its performance for various algorithms before the system is built. However, simulators are limited in the number of cores and threads they can simulate, because of their low simulation speed, high resource usage and poor scalability. Therefore, it is practically impossible to simulate PIUMA at its full system scale. In this paper, we present downscaled simulation, a technique to project performance of a large scale system using a small scale simulation. We apply the technique to PIUMA, showing how to configure the downscaled system in order to accurately reflect the characteristics of the full system. We evaluate downscaled simulation on a set of graph applications, showing that it accurately tracks simulation results of small scale simulations, as well as the projections to large systems made by an analytical model.
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