cuFFT is the only CUDA component linked dynamically (cudart and the
fast-feedback indexer are static), so the prior Windows installer would
fail to launch the GPU path on a host without a CUDA toolkit. Ship
cufft64_*.dll next to the viewer (CUDA 13 keeps it in bin/x64, earlier
toolkits in bin); the DLL is self-contained, so the installed app needs
only an NVIDIA driver.
Tag the variant where it matters and nowhere else: the installer
filename (-cuda<major> / -cpu) and the Add/Remove Programs entry
("Jungfraujoch (CUDA)" / "(CPU)") advertise it, while the install folder
and Start Menu group stay plain "Jungfraujoch" -- the CUDA build is a
strict superset, so the two variants share a location and replace each
other.
Docs: SOFTWARE.md + JFJOCH_VIEWER.md.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Revert Eigen from the FetchContent OVERRIDE_FIND_PACKAGE vendoring (cd394c52,
d4d2d0d8) back to an external find_package(Eigen3) dependency, like zlib. The
OVERRIDE_FIND_PACKAGE mechanism makes the Visual-Studio-bundled CMake (4.x
"-msvc") intermittently segfault during configure -- ~1/3 of fresh configures,
and 100% with Ceres CUDA enabled. The fault is in CMake's own FetchContent
variable-stack cleanup, reached when Ceres' find_package(Eigen3) resolves the
override through a nested FetchContent_MakeAvailable. Stock Kitware CMake runs
the identical scripts fine, so it is a bug in the VS-bundled cmake binary;
providing Eigen externally avoids that path entirely and is stable with Ceres
CUDA both on and off (verified 0 crashes; full CUDA build + NSIS installer
succeed under the VS-bundled cmake).
Also fix CPACK_NSIS_INSTALLED_ICON_NAME: the backslash value was written
verbatim into CPackConfig.cmake, where "\j" is an invalid escape that cmake 4.x
(CMP0010 strict) rejects when cpack re-parses it, so cpack failed under the
VS-bundled cmake (older/Kitware cpack only warned). Use a forward slash.
- image_analysis: keep Ceres USE_CUDA OFF (Jungfraujoch does not use Ceres' GPU
solvers) but drop the now-obsolete "required to avoid the Windows cmake crash"
rationale from the comment.
- docs: Eigen is a required external dependency again (SOFTWARE.md); the Windows
viewer build provides zlib + Eigen externally (JFJOCH_VIEWER.md).
- THIRD_PARTY_NOTICES: move Eigen from the fetched-and-linked table to the
external runtime-libraries table.
Docker images still need Eigen re-added (5.0.1, source build) -- to follow.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Acknowledge all bundled third-party software and satisfy attribution/notice
requirements, while keeping it maintainable:
- THIRD_PARTY_NOTICES.md: human-readable manifest (component, copyright, SPDX
license, link) for fetched, vendored, and runtime/SDK dependencies.
- licenses/: verbatim license texts; COLLECT.sh regenerates them from the
build trees and system SDK locations.
- Bundle the verbatim Qt LGPL-3.0 text and the CUDA Toolkit 12.8 EULA.
- frontend: self-contained npm attribution generator (`npm run licenses` ->
dist/THIRD_PARTY_LICENSES.txt), wired into the frontend build target.
- Install LICENSE + notices + licenses/ into share/doc/jfjoch for every
packaged component.
- viewer: Help > "Third-party Licenses" window (QTextBrowser) showing a
generated, self-contained HTML built from licenses/.
- docs/SOFTWARE.md: drop the stale hand-kept dependency lists; point at the
manifest.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
NUMA CPU/memory pinning is no longer worthwhile: the FPGA DMA buffers are
placed device-local by the kernel (dma_alloc_coherent), the big RAM ring
buffer is random-access (first-touch handles placement), and GPU work is
already spread across all visible devices. So drop the pinning entirely
and with it libnuma.
- Delete NUMAHWPolicy; the only concern worth keeping - GPU selection -
is done directly via pin_gpu() (round-robin over visible GPUs) in the
indexer pool and the Lite analysis threads. CPU-only threads
(FPGA acquire/pedestal/summation/frame-transform) no longer bind
anything.
- Drop get_gpu_numa_node() (sysfs lookup) - only SelectGPUAndItsNUMA
used it.
- numa_policy broker setting is deprecated and ignored (kept in the API
for backward compatibility; warns once on startup).
- Remove NUMA_LIBRARY / numa.h / numaif.h detection from CMake.
- Docs: drop the NUMA dependency, remove the numa_policy config example,
and document running multiple brokers on disjoint GPUs via
CUDA_VISIBLE_DEVICES.
- Remove NUMA_GPU_REVIEW.md (the planning note; this work is now done).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
This is an UNSTABLE release. The release has significant modifications and bug fixes, if things go wrong, it is better to revert to 1.0.0-rc.132.
* Support for newer CUDA architectures (notably Blackwell); minimum CUDA version 12.8
* Minor changes to jfjoch_process, jfjoch_fpga_test and jfjoch_lite_perf_test to make them more consistent
Reviewed-on: #52
Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch>
Co-committed-by: Filip Leonarski <filip.leonarski@psi.ch>
This is an UNSTABLE release. The release has significant modifications and bug fixes, if things go wrong, it is better to revert to 1.0.0-rc.132.
* jfjoch_broker: Use httplib for HTTP server instead of Pistache
* jfjoch_broker: Drop OpenSSL support
* jfjoch_broker: Base work for multi-lattice support in the future
* Update dependencies to more recent versions (spdlog, HDF5, Catch2, httplib)
Reviewed-on: #41
This is an UNSTABLE release.
* Fixes in CI pipeline
* jfjoch_broker: Remove PNG preview, no dependency on libpng
* jfjoch_writer: Fix UTC timestamp being generated wrong (mix between milli- and microseconds)
* jfjoch_viewer: Show data collection time in dataset tooltip
* jfjoch_viewer: Allow to choose the calibrant (presets for LaB6 and silver behenate)
* jfjoch_viewer: Auto foreground value
* Use external libjpeg-turbo and libtiff: simpler build stack, these are built and linked statically in automated Docker builds
* Remove OpenBLAS dependency
Reviewed-on: #1
Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch>
Co-committed-by: Filip Leonarski <filip.leonarski@psi.ch>
leonarski_fandClaude Opus 4.8