NVIDIA Jetson Platform Characterization
NVIDIA Jetson Platform Characterization
复制标题
NVIDIA Jetson 平台特征
DOI：
--
复制
发表时间：
2017
期刊：
影响因子：
--
通讯作者：
M. Ripeanu
中科院分区：
文献类型：
--
作者：
Hassan Halawa;Hazem A. Abdelhafez;Andrew Boktor;M. Ripeanu
这项研究表征了NVIDIA JETSON TK1和TX1平台，这些平台都建立在芯片上的NVIDIA TEGRA系统上，并结合了四核ARM CPU和NVIDIA GPU。申请开发人员推理性能并确定哪些优化值得追求。通过基于经验测量的方法以及通过异质应用的案例研究获得的平台性能（矩阵乘法），我们的结果突出了CPU和GPU之间的计算性能的差异。在两个平台上，CPU和GPU共享相同的内存总线，他们的车顶模型的平衡点也不仅仅是相隔的数量级。我们还探讨了频率缩放的影响：构建CPU和GPU车顶线轮廓，并表征两个平台的平衡点变化，功耗和每瓦的性能，并随着频率的缩放而表征。
This study characterizes the NVIDIA Jetson TK1 and TX1 Platforms, both built on a NVIDIA Tegra System on Chip and combining a quad-core ARM CPU and an NVIDIA GPU. Their heterogeneous nature, as well as their wide operating frequency range, make it hard for application developers to reason about performance and determine which optimizations are worth pursuing. This paper attempts to inform developers’ choices by characterizing the platforms’ performance using Roofline models obtained through an empirical measurement-based approach as well as through a case study of a heterogeneous application (matrix multiplication). Our results highlight a difference of more than an order of magnitude in compute performance between the CPU and GPU on both platforms. Given that the CPU and GPU share the same memory bus, their Roofline models’ balance points are also more than an order of magnitude apart. We also explore the impact of frequency scaling: build CPU and GPU Roofline profiles and characterize both platforms’ balance point variation, power consumption, and performance per watt as frequency is scaled.