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README Update, main branch (2024.05.07.) #577

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README Update, main branch (2024.05.07.) #577

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30 changes: 15 additions & 15 deletions README.md
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Expand Up @@ -4,16 +4,16 @@ Demonstrator tracking chain for accelerators.

## Features

| Category | Algorithms | CPU | CUDA | SYCL | Futhark |
| ------------------ | ---------------------- | --- | ---- | ---- | ------- |
| **Clusterization** | CCL | ✅ | ✅ | ✅ | ✅ |
| | Measurement creation | ✅ | ✅ | ✅ | ✅ |
| **Seeding** | Spacepoint formation | ✅ | ✅ | ✅ | ⚪ |
| | Spacepoint binning | ✅ | ✅ | ✅ | ⚪ |
| | Seed finding | ✅ | ✅ | ✅ | ⚪ |
| | Track param estimation | ✅ | ✅ | ✅ | ⚪ |
| **Track finding** | Combinatorial KF | ✅ | ✅ | 🟡 | ⚪ |
| **Track fitting** | KF | ✅ | ✅ | ✅ | ⚪ |
| Category | Algorithms | CPU | CUDA | SYCL | Alpaka | Kokkos | Futhark |
| ------------------ | ---------------------- | --- | ---- | ---- | ------ | ------ | ------- |
| **Clusterization** | CCL / FastSv / etc. | ✅ | ✅ | ✅ | 🟡 | ⚪ | ✅ |
| | Measurement creation | ✅ | ✅ | ✅ | 🟡 | ⚪ | ✅ |
| **Seeding** | Spacepoint formation | ✅ | ✅ | ✅ | 🟡 | ⚪ | ⚪ |
| | Spacepoint binning | ✅ | ✅ | ✅ | ✅ | ✅ | ⚪ |
| | Seed finding | ✅ | ✅ | ✅ | ✅ | ⚪ | ⚪ |
| | Track param estimation | ✅ | ✅ | ✅ | ✅ | ⚪ | ⚪ |
| **Track finding** | Combinatorial KF | ✅ | ✅ | 🟡 | 🟡 | ⚪ | ⚪ |
| **Track fitting** | KF | ✅ | ✅ | ✅ | ⚪ | ⚪ | ⚪ |

✅: exists, 🟡: work started, ⚪: work not started yet

Expand Down Expand Up @@ -265,7 +265,7 @@ Users can generate muon-like particle simulation data with the pre-built detray

```sh
# Generate telescope geometry data
<build_directory>/bin/traccc_simulate_telescope --gen-vertex-xyz-mm=0:0:0 --gen-vertex-xyz-std-mm=0:0:0 --gen-mom-gev=100:100 --gen-phi-degree=0:0 --events=10 --gen-nparticles=2000 --output-directory=detray_simulation/telescope_detector/n_particles_2000/ --gen-eta=1:3
<build_directory>/bin/traccc_simulate_telescope --gen-vertex-xyz-mm=0:0:0 --gen-vertex-xyz-std-mm=0:0:0 --gen-mom-gev=100:100 --gen-phi-degree=0:0 --events=10 --gen-nparticles=2000 --output-directory=detray_simulation/telescope_detector/n_particles_2000/ --gen-eta=1:3

# Generate toy geometry data
<build_directory>/bin/traccc_simulate_toy_detector --gen-vertex-xyz-mm=0:0:0 --gen-vertex-xyz-std-mm=0:0:0 --gen-mom-gev=100:100 --gen-phi-degree=0:360 --events=10 --gen-nparticles=2000 --output-directory=detray_simulation/toy_detector/n_particles_2000/ --gen-eta=-3:3 --constraint-step-size-mm=1 --search-window 3 3
Expand All @@ -276,7 +276,7 @@ Users can generate muon-like particle simulation data with the pre-built detray

The simulation will also generate the detector json files (geometry, material and surface_grid) in the current directory. It is user's responsibility to move them to an appropriate place (e.g. `<detector_directory>`) and match them to the input file arguments of reconstruction chains.

If users have a geometry json file already, it is also possible to run simulation with `traccc_simulate` application
If users have a geometry json file already, it is also possible to run simulation with `traccc_simulate` application

```sh
# Given that users have a geometry json file
Expand All @@ -291,7 +291,7 @@ There are three types of partial reconstruction chain users can operate: `seedin
| `truth_finding_example` | | | ✅ | ✅ |
| `truth_fitting_example` | | | | ✅ |

The dirft chamber will not produce meaningful results with `seeding_example` as the current seeding algorithm is only designed for 2D measurement objects. Truth finding works OK in general but the combinatoric explosion can occur for a few unlucky events, leading to poor pull value distributions. The followings are example commands:
The dirft chamber will not produce meaningful results with `seeding_example` as the current seeding algorithm is only designed for 2D measurement objects. Truth finding works OK in general but the combinatoric explosion can occur for a few unlucky events, leading to poor pull value distributions. The followings are example commands:

```sh
# Run cuda seeding example for toy geometry
Expand All @@ -316,8 +316,8 @@ The dirft chamber will not produce meaningful results with `seeding_example` as
Users can open the performance root files (with `--check-performance=true`) and draw the histograms.

```sh
$ root -l performance_track_finding.root
root [0]
$ root -l performance_track_finding.root
root [0]
Attaching file performance_track_finding.root as _file0...
(TFile *) 0x3871910
root [1] finding_trackeff_vs_eta->Draw()
Expand Down
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