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Benchmarking the Memory Hierarchy of Modern GPUs

  • Xinxin Mei
  • Kaiyong Zhao
  • Chengjian Liu
  • Xiaowen Chu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8707)

Abstract

Memory access efficiency is a key factor for fully exploiting the computational power of Graphics Processing Units (GPUs). However, many details of the GPU memory hierarchy are not released by the vendors. We propose a novel fine-grained benchmarking approach and apply it on two popular GPUs, namely Fermi and Kepler, to expose the previously unknown characteristics of their memory hierarchies. Specifically, we investigate the structures of different cache systems, such as data cache, texture cache, and the translation lookaside buffer (TLB). We also investigate the impact of bank conflict on shared memory access latency. Our benchmarking results offer a better understanding on the mysterious GPU memory hierarchy, which can help in the software optimization and the modelling of GPU architectures. Our source code and experimental results are publicly available.

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Copyright information

© IFIP International Federation for Information Processing 2014

Authors and Affiliations

  • Xinxin Mei
    • 1
  • Kaiyong Zhao
    • 1
  • Chengjian Liu
    • 1
  • Xiaowen Chu
    • 1
  1. 1.Department of Computer ScienceHong Kong Baptist UniversityHong Kong

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