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Benchmarks

The test file information are listed below:

Index Filename Number of Cells Dimension AMR Public
1 1d_single.vlsv 20 1 No Yes
2 bulk.2d.vlsv 6,300 1 No Yes
3 2d_double.vlsv 51,200 2 No Yes
4 2d_AFC.vlsv 4,612,500 2 No Yes
5 3d_EGI.vlsv 3,966,580 3 Yes No

Access to the public data can be found from vlsv_data.

!!! note The numbers shown here are comparisons between Analysator v0.9 and Vlasiator.jl v0.9.32 running Python 3.6.9/3.9.7 and Julia 1.8.3 with the scripts perf.jl and perf.py. The timings are collected from a i5-10210U @ 1.6GHz CPU with 16 GB RAM if not specified.

  • Loading meta data1 | File Index | Julia [ms] | Python [ms] | Ratio | |:-----------|:----------:|:-----------:|:-----:| | 1 | 0.18 | 1.19 | 6.6 | | 2 | 0.51 | 1.66 | 3.1 | | 3 | 2.33 | 3.11 | 1.3 | | 4 | 506 | 277 | 0.5 | | 5 | 549 | 283 | 0.5 |
  • Reading DCCRG grid variables | File Index | Julia [ms] | Python [ms] | Ratio | |:-----------|:----------:|:-----------:|:------:| | 1 | 0.004 | 0.07 | 17 | | 2 | 0.022 | 0.08 | 4 | | 3 | 0.172 | 0.21 | 1.2 | | 4 | 202 | 23 | 1.1 | | 5 | 112 | 11 | 1.0 |
  • Reading field solver grid variables3 | File Index | Size | Julia [s] | Julia, mmap [s] | Python [s] | Ratio | |:-----------|:----------------|:---------:|:---------------:|:----------:|:-----:| | 5 | 6.2 GiB Float32 | 18 | 8 | 56 | 7 |

  • Plotting 2D density contours on a uniform mesh (no GUI) | File Index | Julia [s] | Python [s] | Ratio | |:-----------|:---------:|:----------:|:-----:| | 4 | 0.5 | 5.4 | 11 |

  • Plotting 2D density slices from a 3D AMR mesh (no GUI) | File Index | Julia [s]4 | Python [s] | Ratio | |:-----------|:-------------:|:----------:|:-----:| | 5 | 0.5 | 3.1 | 6.2 |

  • Static virtual satellite tracking from 3D AMR data (26G per frame, 32 MB Cell IDs) on a cluster5
Frames Julia, 1 thread [s] Julia, 2 threads [s] Python [s]
845 45 34 1220

Footnotes

  1. See the issue about sorting. The performance of EzXML is also not ideal: we may need to find a better XML parser in Julia. ↩

  2. Vlasiator.jl can be faster if there is no conversion from Float64 to Float32. See Precision. ↩ ↩2 ↩3 ↩4

  3. The field solver grid is a regular Cartesian grid at the finest refinement level introduced after Vlasiator 5. Therefore fsgrid variables are quite large for 3D AMR runs: with limited memory (e.g. 16 GB RAM) you may encounter out-of-memory issues when reading fg_b more than once. In Vlasiator.jl, we provide the option usemmap=true for reading large arrays --- see Memory for more. ↩

  4. The first time execution will be slower due to JIT compilation (which is excluded in the timing here). This is known as "Time-To-First-X" in the Julia community. ↩

  5. University of Helsinki cluster Vorna with Intel Xeon E5-2697 @ 2.70GHz. ↩