WarpX Accelerated Nodes Parallel Computing Paper

This dataset contains the inputs, outputs, job submission scripts, and executables
used to create the Figures in "Porting WarpX to GPU-accelerated platforms" by A. Myers
et. al, submitted to Parallel Computing as part of the ECP Special Issue on Transitioning
to Accelerated nodes.

These results were obtained using the October, 2020 release tags of WarpX and AMReX,
available on Github here:

    https://github.com/ECP-WarpX/WarpX

and here:

    https://github.com/AMReX-Codes/amrex

The following module files were loaded on Summit:

  1) hsi/5.0.2.p5   2) xalt/1.2.0   3) lsf-tools/2.0   4) darshan-runtime/3.1.7
  5) DefApps   6) cuda/10.1.243   7) gcc/6.4.0   8) spectrum-mpi/10.3.1.2-20200121

To use nsight-compute for the roofline plots, we also loaded:

   nsight-compute/2020.1.2

Manifest:

BinScan: contains material used to make Figure 1. To generate the figure, use the
Jupyter notebook called "bin_size.ipynb".

StrongScaling: contains material used to make Figure 5. To generate the figure, use the
Jupyter notebook called "strong_scaling.ipynb".

WeakScalingCPU: contains material used to make Figure 4. To generate the figure, use the
Jupyter notebook called "weak_scaling.ipynb".

WeakScalingGPU: contains material used to make Figure 5. To generate the figure, use the
Jupyter notebook called "weak_scaling.ipynb".

Roofline: contains material used to make the roofline plots (Figures 2 and 3). This
includes output generated using nsight-compute with WarpX and python scripts for
processing and plotting these output files. These scripts and methodology originally
come from Charlene Yang at NERSC. The file "script.sh" was used to generate the
profiler output