Plugins¶
Plugin name |
short description |
---|---|
outputs simulation data via the openPMD API |
|
energy histograms for electrons and ions |
|
maximum difference between electron charge density and div E |
|
stores the primary data of the simulation for restarts. |
|
count total number of macro particles |
|
count macro particles per supercell |
|
electromagnetic field energy per time step |
|
kinetic and total energies summed over all electrons and/or ions |
|
interactive 3D live visualization [Matthes2016] |
|
maximum and integrated electric field along the y-direction |
|
spatially resolved, particle energy detector in infinite distance |
|
macro particle merging |
|
calculate 2D phase space [Huebl2014] |
|
pictures of 2D slices |
|
save trajectory, momentum, … of a single particle |
|
compute emitted electromagnetic spectra [Pausch2012] [Pausch2014] [Pausch2018] |
|
monitor used hardware resources & memory |
|
compute emittance and slice emittance of particles |
|
print out a slice of the electric and/or magnetic and/or current field |
|
compute the total current summed over all cells |
|
compute emitted electromagnetic spectra |
|
compute SAXS scattering amplitude ( based on FieldTmp species density ) |
Footnotes
- 1(1,2)
On restart, plugins with that footnote overwrite their output of previous runs. Manually save the created files of these plugins before restarting in the same directory.
- 2(1,2,3,4,5,6,7)
Requires PIConGPU to be compiled with openPMD API.
- 3
Can remember particles that left the box at a certain time step.
- 4(1,2,3)
Deprecated
- 5(1,2,3,4,5,6,7,8)
Only runs on the CUDA backend (GPU).
- 6(1,2,3,4,5,6)
Multi-Plugin: Can be configured to run multiple times with varying parameters.
Period Syntax¶
Most plugins allow to define a period on how often a plugin shall be executed (notified).
Its simple syntax is: <period>
with a simple number.
Additionally, the following syntax allows to define intervals for periods:
<start>:<end>[:<period>]
<start>: begin of the interval; default: 0
<end>: end of the interval, including the upper bound; default: end of the simulation
<period>: notify period within the interval; default: 1
Multiple intervals can be combined via a comma separated list.
Examples¶
42
every 42th time step::
equal to just writing1
, every time step from start (0) to the end of the simulation11:11
only once at time step 1110:100:2
every second time step between steps 10 and 100 (included)42,30:50:10
: at steps 30 40 42 50 84 126 168 …5,10
: at steps 0 5 10 15 20 25 … (only executed once per step in overlapping intervals)
Python Postprocessing¶
In order to further work with the data produced by a plugin during a simulation run, PIConGPU provides python tools that can be used for reading data and visualization.
They can be found under lib/python/picongpu/plugins
.
It is our goal to provide at least three modules for each plugin to make postprocessing as convenient as possible:
1. a data reader (inside the data
subdirectory)
2. a matplotlib visualizer (inside the plot_mpl
subdirectory)
3. a jupyter widget visualizer (inside the jupyter_widgets
subdirectory) for usage in jupyter-notebooks
Further information on how to use these tools can be found at each plugin page.
If you would like to help in developing those classes for a plugin of your choice, please read python postprocessing.
References
- Huebl2014
A. Huebl. Injection Control for Electrons in Laser-Driven Plasma Wakes on the Femtosecond Time Scale, Diploma Thesis at TU Dresden & Helmholtz-Zentrum Dresden - Rossendorf for the German Degree “Diplom-Physiker” (2014), DOI:10.5281/zenodo.15924
- Matthes2016
A. Matthes, A. Huebl, R. Widera, S. Grottel, S. Gumhold, and M. Bussmann In situ, steerable, hardware-independent and data-structure agnostic visualization with ISAAC, Supercomputing Frontiers and Innovations 3.4, pp. 30-48, (2016), arXiv:1611.09048, DOI:10.14529/jsfi160403
- Huebl2017
A. Huebl, R. Widera, F. Schmitt, A. Matthes, N. Podhorszki, J.Y. Choi, S. Klasky, and M. Bussmann. On the Scalability of Data Reduction Techniques in Current and Upcoming HPC Systems from an Application Perspective. ISC High Performance Workshops 2017, LNCS 10524, pp. 15-29 (2017), arXiv:1706.00522, DOI:10.1007/978-3-319-67630-2_2
- Pausch2012
R. Pausch. Electromagnetic Radiation from Relativistic Electrons as Characteristic Signature of their Dynamics, Diploma Thesis at TU Dresden & Helmholtz-Zentrum Dresden - Rossendorf for the German Degree “Diplom-Physiker” (2012), DOI:10.5281/zenodo.843510
- Pausch2014
R. Pausch, A. Debus, R. Widera, K. Steiniger, A.Huebl, H. Burau, M. Bussmann, and U. Schramm. How to test and verify radiation diagnostics simulations within particle-in-cell frameworks, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 740, pp. 250-256 (2014) DOI:10.1016/j.nima.2013.10.073
- Pausch2018
R. Pausch, A. Debus, A. Huebl, U. Schramm, K. Steiniger, R. Widera, and M. Bussmann. Quantitatively consistent computation of coherent and incoherent radiation in particle-in-cell codes - a general form factor formalism for macro-particles, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 909, pp. 419-422 (2018) arXiv:1802.03972, DOI:10.1016/j.nima.2018.02.020