Comparing simulation techniques for microarchitecture-aware floorplanning

Vidyasagar Nookala, Ying Chen, D. Lilja, S. Sapatnekar
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引用次数: 2

Abstract

Due to the long simulation times of the reference input sets, microarchitects resort to alternative techniques to speed up cycle-accurate simulations. However, the reduction in the runtimes comes with an associated loss of accuracy in replicating the characteristics of the reference sets. In addition, the effect of these inaccuracies on the overall performance can vary across different microarchitecture optimizations or enhancements. In this work, we study and compare two such techniques, reduced input sets and statistical sampling, in the context of microarchitecture-aware floorplanning, a physical design stage, where the objective is to find an IPC-optimal global placement of the blocks of a microprocessor. The variation in the IPC results due the insertion of additional flip-flops on some across-chip wires of the processor that have multicycle delays in nanometer technology nodes. The objective of IPC-aware floorplanning is to minimize the amount of pipelining required by the system buses that are critical in determining the system performance. Our results indicate that, although the two techniques exhibit contrasting behavior in quantifying the criticality of bus latencies, the ensuing floorplanning optimization process results in almost identical performance improvements for both reduced input sets and sampling. The reason behind this is that, for discrete optimization problems such as IPC-aware floorplanning, a reasonably accurate relative ordering of performance bottlenecks is sufficient, absolute accuracy is not necessary.
微架构感知平面规划的仿真技术比较
由于参考输入集的模拟时间较长,微架构师采用替代技术来加速周期精确的模拟。然而,运行时的减少带来了复制参考集特征的准确性损失。此外,这些不准确性对整体性能的影响可能因不同的微体系结构优化或增强而异。在这项工作中,我们研究并比较了两种这样的技术,减少输入集和统计抽样,在微架构感知平面规划的背景下,物理设计阶段,其目标是找到ipc最优的微处理器块的全局放置。IPC的变化是由于在处理器的一些跨芯片导线上插入了额外的触发器,这些触发器在纳米技术节点中具有多周期延迟。ipc感知地板规划的目标是最小化系统总线所需的流水线数量,这对确定系统性能至关重要。我们的研究结果表明,尽管这两种技术在量化总线延迟的重要性方面表现出截然不同的行为,但随后的布局优化过程在减少输入集和采样方面的性能改进几乎相同。这背后的原因是,对于离散优化问题,如ipc感知地板规划,性能瓶颈的合理准确的相对排序就足够了,绝对的准确性是不必要的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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