traccc
Demonstrator tracking chain for accelerators.
Features
Category | Algorithms | CPU | CUDA | SYCL | Futhark |
---|---|---|---|---|---|
Clusterization | CCL | ||||
Measurement creation | |||||
Spacepoint formation | |||||
Track finding | Spacepoint binning | ||||
Seed finding | |||||
Track param estimation | |||||
Combinatorial KF | |||||
Track fitting | KF |
The relations between datatypes and algorithms is given in the (approximately commutative) diagram shown below. Black lines indicate CPU algorithms, green lines indicate CUDA algorithms, blue lines indicate SYCL algorithms, and brown lines indicate Futhark algorithms. Solid algorithms are ready for use, dashed algorithms are in development or future goals. Data types for different heterogeneous platforms are contracted for legibility, and identities are hidden.
flowchart LR
subgraph clusterization [<a href='https://github.com/acts-project/traccc/blob/main/core/include/traccc/clusterization/clusterization_algorithm.hpp'>Clusterization</a>]
direction TB
cell(Cells);
cluster(Clusters);
meas(Measurements);
end
subgraph trkfinding [Track Finding]
sp(Spacepoints);
bin(Bins);
seed(Seeds);
ptrack(Prototracks);
end
subgraph trkfitting [Track Fitting]
track(Track);
end
click cell href "https://github.com/acts-project/traccc/blob/main/core/include/traccc/edm/cell.hpp";
click cluster href "https://github.com/acts-project/traccc/blob/main/core/include/traccc/edm/cluster.hpp";
click meas href "https://github.com/acts-project/traccc/blob/main/core/include/traccc/edm/measurement.hpp";
click sp href "https://github.com/acts-project/traccc/blob/main/core/include/traccc/edm/spacepoint.hpp";
click seed href "https://github.com/acts-project/traccc/blob/main/core/include/traccc/edm/seed.hpp";
click ptrack href "https://github.com/acts-project/traccc/blob/main/core/include/traccc/edm/track_parameters.hpp";
%% CPU CCL algorithm
cell -->|<a href='https://github.com/acts-project/traccc/blob/main/core/include/traccc/clusterization/component_connection.hpp'>CCL</a>| cluster;
linkStyle 0 stroke: black;
%% SYCL CCL algorithm
cell -->|CCL| cluster;
linkStyle 1 stroke: blue;
%% CUDA CCL algorithm
cell -->|CCL| cluster;
linkStyle 2 stroke: green;
%% CPU clusterization
cluster -->|<a href='https://github.com/acts-project/traccc/blob/main/core/include/traccc/clusterization/measurement_creation.hpp'>Agg.</a>| meas;
linkStyle 3 stroke: black;
%% SYCL clusterization
cluster -->|Agg.| meas;
linkStyle 4 stroke: blue;
%% CUDA clusterization
cluster -->|Agg.| meas;
linkStyle 5 stroke: green;
%% CUDA CCA
cell -->|CCA| meas;
linkStyle 6 stroke: green;
%% CPU local to global
meas -->|<a href='https://github.com/acts-project/traccc/blob/main/core/include/traccc/clusterization/spacepoint_formation.hpp'>L2G</a>| sp;
linkStyle 7 stroke: black;
%% SYCL local to global
meas -->|L2G| sp;
linkStyle 8 stroke: blue;
%% CUDA local to global
meas -->|L2G| sp;
linkStyle 9 stroke: green;
%% CPU binning
sp -->|<a href='https://github.com/acts-project/traccc/blob/main/core/include/traccc/seeding/spacepoint_binning.hpp'>Binning</a>| bin;
linkStyle 10 stroke: black;
%% CUDA binning
sp -->|<a href='https://github.com/acts-project/traccc/blob/main/device/cuda/include/traccc/cuda/seeding/spacepoint_binning.hpp'>Binning</a>| bin;
linkStyle 11 stroke: green;
%% CPU seeding
bin -->|Seeding| seed;
linkStyle 12 stroke: black;
%% SYCL seeding
bin -->|<a href='https://github.com/acts-project/traccc/blob/main/device/sycl/include/traccc/sycl/seeding/seed_finding.hpp'>Seeding</a>| seed;
linkStyle 13 stroke: blue;
%% CUDA seeding
bin -->|<a href='https://github.com/acts-project/traccc/tree/main/device/cuda/include/traccc/cuda/seeding'>Seeding</a>| seed;
linkStyle 14 stroke: green;
%% CUDA binless seeding
sp -.->|Seeding| seed;
linkStyle 15 stroke: green;
%% CPU param est.
seed -->|<a href='https://github.com/acts-project/traccc/blob/main/core/include/traccc/seeding/track_params_estimation.hpp'>Param. Est.</a>| ptrack;
linkStyle 16 stroke: black;
%% CUDA param est.
seed -->|<a href='https://github.com/acts-project/traccc/blob/main/device/cuda/include/traccc/cuda/seeding/track_params_estimation.hpp'>Param. Est.</a>| ptrack;
linkStyle 17 stroke: green;
%% CPU CKF
ptrack -.->|CKF| track;
linkStyle 18 stroke: black;
%% CPU Kalman filter
track -.->|Kalman filter| track;
linkStyle 19 stroke: black;
%% CUDA kalman filter
track -.->|Kalman filter| track;
linkStyle 20 stroke: green;
%% SYCL binning
sp -->|<a href='https://github.com/acts-project/traccc/blob/main/device/sycl/include/traccc/sycl/seeding/spacepoint_binning.hpp'>Binning</a>| bin;
linkStyle 21 stroke: blue;
%% SYCL track parameter est.
seed -->|<a href='https://github.com/acts-project/traccc/blob/main/device/sycl/include/traccc/sycl/seeding/track_params_estimation.hpp'>Param. Est.</a>| ptrack;
linkStyle 22 stroke: blue;
%% Futhark measurement creation
cell -->|<a href='https://github.com/acts-project/traccc/blob/main/device/futhark/src/measurement_creation.fut'>CCA</a>| meas;
linkStyle 23 stroke: brown;
%% Futhark spacepoint creation
meas -->|<a href='https://github.com/acts-project/traccc/blob/main/device/futhark/src/spacepoint_formation.fut'>L2G</a>| sp;
linkStyle 24 stroke: brown;
Requirements and dependencies
OS & compilers:
Please note that due to the complexity of this software and its build system, it may be somewhat fragile in the face of compiler version changes. The following are general guidelines for getting traccc to compile:
- The C++ compiler must support C++17
In addition, the following requirements hold when CUDA is enabled:
- The CUDA Toolkit version must be greater than major version 11
- The CUDA Toolkit must not be minor version 11.3 due to a bug in the front-end compiler of that version
- Ensure that the CUDA host compiler supports C++17 and is compatible with the
nvcc
compiler driver
The following table lists currently combinations of builds, compilers, and toolchains that are currently known to work (last updated 2022/01/24):
Build | OS | gcc | cuda | comment |
---|---|---|---|---|
CUDA | Ubuntu 20.04 | 9.3.0 | 11.5 | runs on CI |
Data directory
The data
directory is a submodule hosted as git lfs
on https://gitlab.cern.ch/acts/traccc-data
Prerequisites
Getting started
Clone the repository
Clone the repository and setup up the submodules, this requires git-lfs
for the data from the traccc-data
repository.
git clone git@github.com:acts-project/traccc.git
cd traccc
git submodule update --init
Build the project
cmake -S . -B <build_directory>
cmake --build <build_directory> <options>
Build options
Option | Description |
---|---|
TRACCC_BUILD_CUDA | Build the CUDA sources included in traccc |
TRACCC_BUILD_SYCL | Build the SYCL sources included in traccc |
TRACCC_BUILD_TESTING | Build the (unit) tests of traccc |
TRACCC_BUILD_EXAMPLES | Build the examples of traccc |
TRACCC_USE_SYSTEM_VECMEM | Pick up an existing installation of VecMem from the build environment |
TRACCC_USE_SYSTEM_EIGEN3 | Pick up an existing installation of Eigen3 from the build environment |
TRACCC_USE_SYSTEM_ALGEBRA_PLUGINS | Pick up an existing installation of Algebra Plugins from the build environment |
TRACCC_USE_SYSTEM_DFELIBS | Pick up an existing installation of dfelibs from the build environment |
TRACCC_USE_SYSTEM_DETRAY | Pick up an existing installation of Detray from the build environment |
TRACCC_USE_SYSTEM_ACTS | Pick up an existing installation of Acts from the build environment |
TRACCC_USE_SYSTEM_GOOGLETEST | Pick up an existing installation of GoogleTest from the build environment |
Examples
cpu reconstruction chain
<build_directory>/bin/traccc_seq_example --detector_file=tml_detector/trackml-detector.csv --digitization_config_file=tml_detector/default-geometric-config-generic.json --input_directory=tml_pixels/ --events=10
cuda reconstruction chain
- Users can generate cuda examples by adding
-DTRACCC_BUILD_CUDA=ON
to cmake options
<build_directory>/bin/traccc_seq_example_cuda --detector_file=tml_detector/trackml-detector.csv --digitization_config_file=tml_detector/default-geometric-config-generic.json --input_directory=tml_pixels/ --events=10 --run_cpu=1
Troubleshooting
The following are potentially useful instructions for troubleshooting various problems with your build:
CUDA
Incompatible host compiler
You may experience errors being issued about standard library features, for example:
/usr/include/c++/11/bits/std_function.h:435:145: note: ‘_ArgTypes’
/usr/include/c++/11/bits/std_function.h:530:146: error: parameter packs not expanded with ‘...’:
530 | operator=(_Functor&& __f)
In this case, your nvcc
host compiler is most likely incompatible with your
CUDA toolkit. Consider installing a supported version and selecting it through
the CUDAHOSTCXX
environment variable at build-time.