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	🟡	🟡	⚪	⚪

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

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;

    %% CPU clusterization
    cluster -->|<a href='https://github.com/acts-project/traccc/blob/main/core/include/traccc/clusterization/measurement_creation.hpp'>Agg.</a>| meas;
    linkStyle 2 stroke: black;

    %% SYCL clusterization
    cluster -.->|Agg.| meas;
    linkStyle 3 stroke: blue;

    %% CUDA CCA
    cell -.->|CCA| meas;
    linkStyle 4 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 5 stroke: black;

    %% SYCL local to global
    meas -.->|L2G| sp;
    linkStyle 6 stroke: blue;

    %% CUDA local to global
    meas -.->|L2G| sp;
    linkStyle 7 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 8 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 9 stroke: green;

    %% CPU seeding
    bin -.->|Seeding| seed;
    linkStyle 10 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 11 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 12 stroke: green;

    %% CUDA binless seeding
    sp -.->|Seeding| seed;
    linkStyle 13 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 14 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 15 stroke: green;

    %% CPU CKF
    ptrack -.->|CKF| track;
    linkStyle 16 stroke: black;

    %% CPU Kalman filter
    track -.->|Kalman filter| track;
    linkStyle 17 stroke: black;

    %% CUDA kalman filter
    track -.->|Kalman filter| track;
    linkStyle 18 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 19 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 20 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 21 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

Boost: program_options
ROOT: RIO, Hist, Tree

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.

Name		Name	Last commit message	Last commit date
Latest commit History 624 Commits
.githooks		.githooks
.github		.github
cmake		cmake
core		core
data @ 92fde47		data @ 92fde47
device		device
doc/images		doc/images
examples		examples
extern		extern
extras		extras
io		io
plugins		plugins
tests		tests
.clang-format		.clang-format
.gitattributes		.gitattributes
.gitignore		.gitignore
.gitmodules		.gitmodules
.policy.yml		.policy.yml
CMakeLists.txt		CMakeLists.txt
LICENSE		LICENSE
README.md		README.md

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traccc

Features

Requirements and dependencies

OS & compilers:

Data directory

Prerequisites

Getting started

Clone the repository

Build the project

Build options

Examples

cpu reconstruction chain

cuda reconstruction chain

Troubleshooting

CUDA

Incompatible host compiler

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traccc

Features

Requirements and dependencies

OS & compilers:

Data directory

Prerequisites

Getting started

Clone the repository

Build the project

Build options

Examples

cpu reconstruction chain

cuda reconstruction chain

Troubleshooting

CUDA

Incompatible host compiler

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