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**Files written by Jungfraujoch now import correctly in DIALS, XDS and pyFAI.** A tilted detector, a grid scan, a still recorded at a goniometer position, and saturated or unreadable pixels were each described in a way that a third-party program acted on wrongly. If you process Jungfraujoch data outside Jungfraujoch, prefer this release to any earlier one. * HDF5: the detector tilt (`rot1`/`rot2`/`rot3`) is exported correctly in the NXmx transformation chain; untilted geometries are unaffected. * HDF5: a still recorded at a goniometer position is no longer read back as a single image, and a grid scan records a stationary spindle so a program that requires a rotation axis can open it. * HDF5: the sample transformation chain is written in mounting order, with a Smargon head position told apart from the spindle, one entry per image, `module_offset` as a float unit vector, and `offset_units` on every offset. * HDF5: saturated, underloaded and unreadable pixels are described so a downstream program masks them - `saturation_value`, `underload_value`, `error_value` and `bit_depth_readout` are written correctly, and a data file missing next to a VDS master reads as the error marker rather than as zero counts. * HDF5: the rotation axis is read back under whatever name it carries, and `mirror_y` records whether the assembled image is mirrored in Y relative to the detector's raw readout. * A grid scan and a goniometer axis can both be set; they are no longer alternatives. * `images_per_file` is chosen from the acquisition when it is not given: a rotation sweep of at most 20000 images goes into a single data file, a grid scan splits on whole fast-axis rows, and stills and serial keep 1000. * The writer refuses a stream whose start message declares a different pixel format than its images carry, and a DECTRIS detector sending signed images is no longer declared unsigned. * The image stream can carry the sample transformation chain (`transformations`, in the END message); a producer that does not send it gets the same chain built by the writer. * rugnux: fixing the space group with `-S` no longer prevents the lattice from being found - a lattice indexed in a different setting is reindexed into that group's own setting, and a run whose crystal does not have that group's lattice stops and names the cell it indexed as, rather than reporting statistics that cannot describe it. * rugnux: the per-image resolution estimate now predicts the resolution the merged data reach rather than the highest-resolution spot found, and is reported as `SPOT_RESOLUTION_ESTIMATE`. * rugnux: two runs of the same command on the same images produce the same merged intensities; the azimuthal profile written alongside them is not yet reproducible in the same way. * rugnux: the offline lattice refinement is bounded by iterations rather than by a wall clock, so a loaded machine can no longer refine to a different lattice; a live acquisition keeps its real-time bound. * rugnux: the detector-frame modulation correction is fitted on a grid spanning the detector, so whether it is applied no longer depends on how far integration reached. * rugnux: the geometry pre-pass no longer writes `<prefix>_01.mtz`, `_01.cif`, `_01.hkl` and `_01_image.dat`; the refined second pass writes those files under `<prefix>`, and that is the result to use. * rugnux: `_process.h5` describes the pixel format of the images it links to, and is written on a thread of its own. * rugnux: the detector geometry is also logged in XDS's convention (`ORGX`/`ORGY`, detector axis vectors, rotation axis), so it can be compared with an XDS refinement. * rugnux: an image integrated in pyFAI through the `.poni` file written by `--mode calibration` comes out with the correct azimuth, and the file declares pyFAI's `orientation`, which needs pyFAI 2024.01 or newer. Radial integration is unchanged. * rugnux: a rotation run is substantially faster throughout - beam-stop detection, first-pass indexing, geometry refinement, integration, scaling and merging - and observations outside the scaling resolution range are dropped as they are ingested. The refined geometry, the space group chosen and the merged statistics are unchanged. * Faster spot finding and indexing, on the broker as well as in rugnux; the spots found and the lattices indexed are unchanged. * A run reserves substantially less GPU memory: nothing is allocated for buffers that are never read, and a worker builds only the engines it uses. * rugnux: with `-N` left at its default the per-image loop of `--mode mx` uses at most 16 workers per GPU, rather than one per hardware thread; an explicit `-N` is obeyed as given. * CUDA 12 builds now contain device code for Volta, so the RHEL 8 packages and the portable Linux `.tgz` run on a V100; the CUDA 13 artefacts (RHEL 9, Ubuntu, Windows) remain Turing and newer. * The build resolves a single Eigen for the whole project, and refuses to configure if Ceres picks up a different one; a build that mixed two Eigen versions was undefined behaviour and crashed at -O2. * Documentation: a security page, and the supported GPU generations and minimum NVIDIA driver version of every released artefact. **Breaking change to OpenAPI** - regenerate the client (`jfjoch-client` 1.0.0-rc.162, `frontend/src/client`): * `dataset_settings.images_per_file` is no longer `default: 1000` and no longer accepts `0`; it is optional, and its minimum is 1. A client sending `0` (previously "one file for the whole run") is now rejected - omit the field instead, which for a rotation sweep gives the same single file. * `file_writer_format` now defaults to `NXmxVDS`, matching the server's own default and the layout recommended for DIALS, XDS and CrystFEL. A generated client that fills in schema defaults and does not set the format explicitly will write VDS masters where it previously wrote legacy ones; set `NXmxLegacy` explicitly to keep them. --------- Co-authored-by: jungfrau <jungfrau@mx-aare-test.psi.ch> Reviewed-on: #72 Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch>
300 lines
12 KiB
C++
300 lines
12 KiB
C++
// SPDX-FileCopyrightText: 2025 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
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// SPDX-License-Identifier: GPL-3.0-only
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#include "IndexerThreadPool.h"
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#include "../common/CUDAWrapper.h"
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#include "../common/Logger.h"
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#ifdef JFJOCH_USE_CUDA
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#include "FFBIDXIndexer.h"
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#include "FFTIndexerGPU.h"
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#endif
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#ifdef JFJOCH_USE_FFTW
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#include "FFTIndexerCPU.h"
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#endif
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void WarmUpCuFFT() {
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#ifdef JFJOCH_USE_CUDA
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if (get_gpu_count() == 0)
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return;
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cufftHandle plan = 0;
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if (cufftPlan1d(&plan, 1024, CUFFT_C2C, 1) == CUFFT_SUCCESS)
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cufftDestroy(plan);
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#endif
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}
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// The indexer for one RESOLVED algorithm, or nullptr if this build/host cannot serve it.
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static std::unique_ptr<Indexer> MakeIndexer(IndexingAlgorithmEnum algorithm, const IndexingSettings &settings) {
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#ifdef JFJOCH_USE_CUDA
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if (get_gpu_count() > 0) {
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if (algorithm == IndexingAlgorithmEnum::FFT)
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return std::make_unique<FFTIndexerGPU>(settings);
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if (algorithm == IndexingAlgorithmEnum::FFBIDX)
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return std::make_unique<FFBIDXIndexer>();
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}
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#endif
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#ifdef JFJOCH_USE_FFTW
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if (algorithm == IndexingAlgorithmEnum::FFTW)
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return std::make_unique<FFTIndexerCPU>(settings);
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#endif
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return nullptr;
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}
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IndexerThread::IndexerThread(const IndexingSettings &settings, int threadid, IndexerConstruction construction)
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: settings_(settings), construction_(construction) {
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std::unique_lock<std::mutex> lock(m);
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state = TaskState::STARTING;
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worker_thread = std::thread(&IndexerThread::Worker, this, threadid);
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c_running.wait(lock, [this] { return state != TaskState::STARTING; });
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if (state == TaskState::ERROR) {
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worker_thread.join();
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throw JFJochException(JFJochExceptionCategory::InputParameterInvalid,
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"Indexer thread initialization failed");
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}
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}
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void IndexerThread::Worker(int threadid) {
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try {
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pin_gpu();
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} catch (const std::exception &e) {
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spdlog::error("Failed to pin to GPU {}", e.what());
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} catch (...) {
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// GPU pinning errors are not critical and should be ignored for the time being.
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}
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std::unique_ptr<Indexer> fft_indexer, ffbidx_indexer, fftw_indexer;
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// Preconstruct: build every indexer the requested algorithm could resolve to before the pool
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// reports ready, so no cuFFT planning happens once frames are flowing, and a failure is fatal
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// for the pool instead of being met frame by frame. OnFirstUse skips this and builds in the
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// dispatch below.
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if (construction_ == IndexerConstruction::Preconstruct) {
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try {
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const auto requested = settings_.GetAlgorithm();
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if (requested == IndexingAlgorithmEnum::Auto || requested == IndexingAlgorithmEnum::FFT)
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fft_indexer = MakeIndexer(IndexingAlgorithmEnum::FFT, settings_);
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if (requested == IndexingAlgorithmEnum::Auto || requested == IndexingAlgorithmEnum::FFBIDX)
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ffbidx_indexer = MakeIndexer(IndexingAlgorithmEnum::FFBIDX, settings_);
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if ((requested == IndexingAlgorithmEnum::Auto && get_gpu_count() == 0)
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|| requested == IndexingAlgorithmEnum::FFTW)
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fftw_indexer = MakeIndexer(IndexingAlgorithmEnum::FFTW, settings_);
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} catch (const std::exception &e) {
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spdlog::error("Failed to initialize indexer: {}", e.what());
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{
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std::unique_lock<std::mutex> lock(m);
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state = TaskState::ERROR;
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}
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c_running.notify_all();
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return;
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} catch (...) {
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spdlog::error("Failed to initialize indexer");
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{
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std::unique_lock<std::mutex> lock(m);
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state = TaskState::ERROR;
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}
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c_running.notify_all();
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return;
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}
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}
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{
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std::unique_lock<std::mutex> lock(m);
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state = TaskState::IDLE;
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}
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c_running.notify_all();
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while (true) {
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std::unique_ptr<TaskInput> input;
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// Look for task + handle stop
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{
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std::unique_lock<std::mutex> lock(m);
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c_start.wait(lock, [this] { return stop || state == TaskState::READY; });
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if (stop && (state != TaskState::READY))
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return;
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state = TaskState::RUNNING;
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input = std::move(task_input);
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}
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if (input) {
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std::unique_ptr<IndexerResult> tmp_result;
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try {
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auto algorithm = input->experiment.GetIndexingAlgorithm();
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std::unique_ptr<Indexer> *slot = nullptr;
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switch (algorithm) {
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case IndexingAlgorithmEnum::FFT: slot = &fft_indexer; break;
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case IndexingAlgorithmEnum::FFBIDX: slot = &ffbidx_indexer; break;
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case IndexingAlgorithmEnum::FFTW: slot = &fftw_indexer; break;
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default: break;
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}
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// A preconstructing worker already holds it; an OnFirstUse worker builds it here,
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// on the first frame that resolves to this algorithm.
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if (slot && !*slot)
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*slot = MakeIndexer(algorithm, settings_);
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if (!slot || !*slot) {
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// Algorithm is already resolved here (never Auto/None - see
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// IndexerThreadPool::Run, which also checked this host can serve it). Reaching
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// this means the resolved algorithm has no matching indexer in this build -
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// fail loudly instead of silently not indexing.
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throw JFJochException(JFJochExceptionCategory::InputParameterInvalid,
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"Internal error: no indexer available for the resolved "
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"indexing algorithm");
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}
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Indexer &indexer = **slot;
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indexer.Setup(input->experiment);
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tmp_result = std::make_unique<IndexerResult>(indexer.Run(input->recip));
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} catch (std::exception &e) {
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tmp_result = nullptr;
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spdlog::error("Indexer thread {} failed: {}", threadid, e.what());
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}
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{
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std::unique_lock<std::mutex> lock(m);
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state = TaskState::COMPLETED;
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result = std::move(tmp_result);
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}
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c_done.notify_all();
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}
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}
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}
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void IndexerThread::Finalize() {
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{
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std::unique_lock<std::mutex> lock(m);
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stop = true;
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}
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c_start.notify_all();
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if (worker_thread.joinable())
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worker_thread.join();
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}
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std::unique_ptr<IndexerResult> IndexerThread::Run(const DiffractionExperiment &experiment,
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const std::vector<Coord> &recip) {
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std::unique_ptr<IndexerResult> tmp_result;
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{
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std::unique_lock<std::mutex> lock(m);
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if (stop)
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return nullptr;
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if (state != TaskState::IDLE)
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return nullptr;
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task_input = std::make_unique<TaskInput>(std::cref(experiment), std::cref(recip));
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state = TaskState::READY;
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}
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c_start.notify_one();
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{
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std::unique_lock<std::mutex> lock(m);
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c_done.wait(lock, [this] { return state == TaskState::COMPLETED; });
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tmp_result = std::move(result);
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state = TaskState::IDLE;
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}
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return tmp_result;
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}
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IndexerThread::~IndexerThread() {
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Finalize();
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}
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IndexerThreadPool::IndexerThreadPool(const IndexingSettings &settings, IndexerConstruction construction)
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: worker_busy(settings.GetIndexingThreads(), 0),
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worker_free_count(settings.GetIndexingThreads()),
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viable_cell_min_spots(settings.GetViableCellMinSpots()),
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blocking(settings.GetBlockingBehavior()) {
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for (size_t i = 0; i < settings.GetIndexingThreads(); ++i)
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tasks.emplace_back(std::make_unique<IndexerThread>(std::cref(settings), i, construction));
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}
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int IndexerThreadPool::GetFreeWorker() {
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std::unique_lock<std::mutex> lock(m);
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if (tasks.size() == 0)
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return -1;
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if (blocking)
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c.wait(lock, [this] { return worker_free_count > 0; });
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for (int i = 0; i < tasks.size(); i++) {
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if (worker_busy[i] == 0) {
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worker_busy[i] = 1;
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worker_free_count--;
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return i;
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}
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}
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return -1;
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}
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IndexerResult IndexerThreadPool::Run(const DiffractionExperiment &experiment, const std::vector<Coord> &recip) {
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const auto algorithm = experiment.GetIndexingAlgorithm();
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if (algorithm == IndexingAlgorithmEnum::None)
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return IndexerResult{.lattice = {}, .indexing_time_s = 0, .executed = false};
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// GetIndexingAlgorithm() must already have resolved Auto to a concrete algorithm;
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// the pool has no policy to resolve it, so Auto here is an upstream contract bug.
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if (algorithm == IndexingAlgorithmEnum::Auto)
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throw JFJochException(JFJochExceptionCategory::InputParameterInvalid,
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"Internal error: indexing algorithm must be resolved (not Auto) "
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"before reaching the indexer pool");
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// The workers built their indexers from the raw requested algorithm, but the algorithm actually
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// dispatched is the RESOLVED one (rotation, for instance, always resolves to the GPU FFT indexer
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// when a GPU is present, ignoring the request). If the resolution lands on an algorithm this host
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// did not build an indexer for, fail here with an explanation instead of the opaque "no indexer
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// available for the resolved algorithm" from deep inside a worker.
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const auto requested = experiment.GetIndexingSettings().GetAlgorithm();
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const bool have_gpu = get_gpu_count() > 0;
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#ifdef JFJOCH_USE_FFTW
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constexpr bool fftw_built = true;
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#else
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constexpr bool fftw_built = false;
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#endif
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const bool servable =
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(algorithm == IndexingAlgorithmEnum::FFT && have_gpu &&
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(requested == IndexingAlgorithmEnum::Auto || requested == IndexingAlgorithmEnum::FFT)) ||
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(algorithm == IndexingAlgorithmEnum::FFBIDX && have_gpu &&
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(requested == IndexingAlgorithmEnum::Auto || requested == IndexingAlgorithmEnum::FFBIDX)) ||
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(algorithm == IndexingAlgorithmEnum::FFTW && fftw_built &&
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((requested == IndexingAlgorithmEnum::Auto && !have_gpu) || requested == IndexingAlgorithmEnum::FFTW));
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if (!servable) {
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std::string msg;
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if (requested == IndexingAlgorithmEnum::FFTW && have_gpu)
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msg = "FFTW is the CPU indexer and is not available on a node with a GPU. Rotation indexing "
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"always uses the GPU FFT indexer here; select FFT or Auto, or run FFTW on a CPU-only node.";
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else if (algorithm == IndexingAlgorithmEnum::FFT && !have_gpu)
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msg = "FFT is the GPU indexer but no GPU is available. Select FFTW or Auto for CPU indexing.";
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else if (algorithm == IndexingAlgorithmEnum::FFBIDX && !have_gpu)
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msg = "FFBIDX is a GPU indexer but no GPU is available. Select FFTW or Auto for CPU indexing.";
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else if (algorithm == IndexingAlgorithmEnum::FFTW)
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msg = "FFTW (CPU) indexing was requested but this build has no FFTW indexer.";
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else
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msg = "the requested indexing algorithm resolved to one with no indexer available on this host.";
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throw JFJochException(JFJochExceptionCategory::InputParameterInvalid,
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"Cannot index: " + msg);
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}
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// Check if there is available worker
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const int task = GetFreeWorker();
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std::unique_ptr<IndexerResult> result;
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if (task >= 0) {
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try {
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result = tasks[task]->Run(experiment, recip);
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} catch (const std::exception &e) {
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spdlog::error("Indexer thread failed: {}", e.what());
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result = nullptr;
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}
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{
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std::unique_lock<std::mutex> lock(m);
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worker_busy[task] = 0;
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worker_free_count++;
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}
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c.notify_one();
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}
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if (result)
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return *result;
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return IndexerResult{.lattice = {}, .indexing_time_s = 0};
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}
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