Performance Analysis of Traditional and Data-Parallel Primitive Implementations of Visualization and Analysis Kernels

@article{Bethel2020PerformanceAO,
  title={Performance Analysis of Traditional and Data-Parallel Primitive Implementations of Visualization and Analysis Kernels},
  author={E. Wes Bethel and David Camp and T. Perciano and Colleen Heinemann},
  journal={ArXiv},
  year={2020},
  volume={abs/2010.02361}
}
Measurements of absolute runtime are useful as a summary of performance when studying parallel visualization and analysis methods on computational platforms of increasing concurrency and complexity. We can obtain even more insights by measuring and examining more detailed measures from hardware performance counters, such as the number of instructions executed by an algorithm implemented in a particular way, the amount of data moved to/from memory, memory hierarchy utilization levels via cache… 

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