leonarski_f
7f2ebd8209
* Rugnux: Rotation processing recovers most of the speed lost since 1.0.0-rc.180; live processing in jfjoch_broker finishes sooner. * Rugnux: More reliable rotation processing and indexing, including small molecules and supercells. * Rugnux: More robust serial data and model refinement; molecular replacement handles multi-chain models. * jfjoch_broker (experimental): Live serial processing keeps the detector geometry fixed for the whole run. * jfjoch_broker: Pixel sum without an FPGA, a mask bit for inactive pixels, and several stability fixes. * jfjoch_broker: Rotation indexing and quick integration moved to rugnux live mode; their API settings are deprecated and ignored. * jfjoch_broker, Rugnux: Azimuthal integration can use logarithmic (log10) Q bins or a given number of bins, set from the API, the web interface and the Rugnux command line. * jfjoch_viewer: Build and display fixes; the README is rewritten. Reviewed-on: #95 Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch>
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Software requirements
Operating system
Recommended operating system is Red Hat Enterprise Linux (RHEL) / Rocky Linux versions 8 or 9. For these operating systems we provide RPMs with pre-built binaries to simplify deployment. On an experimental basis we also build repositories for Ubuntu 22.04 and 24.04.
Running Jungfraujoch on Red Hat Enterprise Linux 7 is currently not tested and not recommended, but likely possible by providing some packages from external repositories.
Two programs additionally run on Windows 11: the desktop viewer jfjoch_viewer, shipped as a
pre-built installer, and rugnux, the offline analysis CLI, shipped as a .zip. Both
can be built from source with Visual Studio 2026 (MSVC) and CUDA 13.3 — the viewer additionally
needs Qt 6.11; see
jfjoch_viewer ▸ Building from source on Windows.
The Windows artefacts bundle the Qt runtime (viewer only) and, on the CUDA builds, the cuFFT DLL, so
end users need neither Qt nor a CUDA toolkit installed — only an NVIDIA GPU driver for the GPU path.
On Linux the portable archives link CUDA entirely statically and so need nothing but the driver.
rugnux is also built for 64-bit Arm Linux (GH200, DGX Spark). The rest of Jungfraujoch is
Linux-only and x86-64-only. See Release contents for the CPU baseline and
CUDA requirements of each released package.
Software dependencies
Required:
- C++20 compiler and C++20 standard library: GCC 11 or newer (checked at configure time; on RHEL/Rocky 8 use gcc-toolset-13), or clang 14+ (Intel OneAPI and AMD AOCC also work)
- CMake version 3.26 or newer + a build tool (GNU make or Ninja)
HDF5, libtiff, zlib and Eigen are downloaded and built automatically by CMake (see the note below), so none of them needs to be installed. Beyond the optional dependencies listed below, no third-party library has to be provided by the host.
Optional:
- CUDA compiler version 12.8 or newer - required for the MX fast feedback indexer and GPU analysis
- Node.js - to build the frontend
- Qt version 6 (for jfjoch_viewer)
Many further dependencies (spdlog, Zstandard, HDF5, slsDetectorPackage, libzmq, libtiff,
FFTW, Ceres with abseil, the fast feedback indexer, Catch2, ...) are downloaded automatically
by CMake and statically linked; building therefore requires network access on the first configure.
zlib (as zlib-ng in its zlib-compatible mode) and Eigen are among them: a copy already on the
machine is used instead if the configure is given -DZLIB_ROOT=<prefix> or -DEigen3_DIR=<dir>.
Others are vendored directly in the source tree. The complete list of third-party components, with
copyright holders, licenses and verbatim license texts, is in
Third-party software notices and the licenses/ directory.