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Jungfraujoch/image_analysis/indexing/IndexerThreadPool.h
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v1.0.0-rc.178 (#88)
* Rugnux: Processes serial crystallography data from XFELs - SACLA (MPCCD), PAL-XFEL and European XFEL (CXI), LCLS (XTC) and SwissFEL Alvra (JUNGFRAU with a CrystFEL module geometry) - with several files or Jungfraujoch master files merged in one run (`rugnux *_master.h5`).
* Rugnux: Stills processing takes a known unit cell and space group as a starting point, finds the beam centre (and, with a cell, the detector distance) from the images, detects the saturation level in other facilities' files and refines the placement of individual detector panels.
* Rugnux: The stills report gives R_split and CC1/2 from frame half-sets, comparable with CrystFEL.
* jfjoch_viewer: Opens the same XFEL file formats.
* Validation: A stills battery checks Rugnux against deposited structures from SACLA, PAL-XFEL, LCLS, European XFEL and SwissFEL.
* Rugnux: More reliable convergence of rotation scaling, and live molecular replacement starts as soon as the model is uploaded.
* jfjoch_broker: Initialize clears the previous dataset's bearer tokens, image buffer and live Rugnux status, and a slow CUDA JIT cache is reported at start.

Reviewed-on: #88
Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch>
2026-10-21 11:20:01 +02:00

144 lines
6.6 KiB
C++

// SPDX-FileCopyrightText: 2025 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
// SPDX-License-Identifier: GPL-3.0-only
#pragma once
#include <thread>
#include <mutex>
#include <condition_variable>
#include <queue>
#include <functional>
#include <future>
#include <vector>
#include <optional>
#include <memory>
#include <latch>
#include "../common/JFJochMessages.h"
#include "../common/DiffractionSpot.h"
#include "../common/DiffractionExperiment.h"
#include "Indexer.h"
// When a worker builds its indexers.
//
// Preconstruct (the default, and what the online service needs): every indexer the requested
// algorithm could resolve to is built while the pool is being constructed, so it is resident and
// planned before the first frame arrives. Building one means a cuFFT plan plus ~0.6 GB of device
// allocation, and the first cuFFT call in a process also pays the library's one-time init (0.3 s
// measured); jfjoch_broker cannot have any of that land on the live data path, so holding an indexer
// the resolved algorithm may never dispatch to is an accepted cost there.
//
// OnFirstUse (offline batch - rugnux, jfjoch_viewer): nothing is latency-critical, so the indexer is
// built on the first frame that needs it. The algorithm is only resolved from the frame's
// DiffractionExperiment (rotation -> FFT, stills with a known cell -> FFBIDX), so preconstructing
// leaves each worker holding a fully allocated FFTIndexerGPU - 0.6 GB of cuFFT plan and histograms -
// that can never be dispatched to.
enum class IndexerConstruction { Preconstruct, OnFirstUse };
// Force cuFFT's one-time library initialisation - 0.3 s measured, paid by whichever call happens to
// be first - so it can be got out of the way on a background thread at startup rather than landing in
// the middle of the first pass with nothing overlapping it. Returns how long a 3D plan takes to make
// after that, in ms - about 1 from a working CUDA JIT cache, 60 or more without (see CudaJitCache.h) -
// and NaN without a GPU.
double WarmUpCuFFT();
// cuFFT plans are kept and reused for as long as one of these lives, and destroyed when the last one
// ends (CudaFFTPlanScope): one per processing run in `rugnux`, so no plan outlives the run that made it;
// one for its lifetime in jfjoch_broker. Nothing without CUDA.
class CudaFFTPlanScope;
class FFTPlanReuse {
std::unique_ptr<CudaFFTPlanScope> scope;
public:
FFTPlanReuse();
~FFTPlanReuse();
FFTPlanReuse(const FFTPlanReuse &) = delete;
FFTPlanReuse &operator=(const FFTPlanReuse &) = delete;
};
// GPU FFT indexers are kept for reuse while one of these is alive, by card and the settings they are
// built from, and destroyed when the last one ends. A pool's worker then borrows a kept indexer instead
// of building one, and gives it back - not to the card - when it ends or is released (ReleaseIndexers):
// the device memory stays taken in between. For jfjoch_broker's rugnux live runs, which build the same
// pools for every pass of every collection; an indexer computes the same with any earlier frames behind
// it, as it does within a pool. Nothing without CUDA.
class FFTIndexerReuse {
public:
FFTIndexerReuse();
~FFTIndexerReuse();
FFTIndexerReuse(const FFTIndexerReuse &) = delete;
FFTIndexerReuse &operator=(const FFTIndexerReuse &) = delete;
};
// Builds `count` GPU FFT indexers of these settings on the current card at the same time, and keeps them
// for the pools that ask for them later (inside an FFTIndexerReuse; outside one they are only built and
// destroyed). Nothing without a GPU.
void KeepFFTIndexers(const IndexingSettings &settings, int count);
class IndexerThread {
struct TaskInput {
const DiffractionExperiment &experiment;
const std::vector<Coord> &recip;
const bool severity_only;
};
// Held by value: with IndexerConstruction::OnFirstUse the worker builds its indexer long after
// the constructor returned, and pools are routinely built from a temporary - for instance
// IndexerThreadPool(experiment.GetIndexingSettings()), which returns by value.
const IndexingSettings settings_;
const IndexerConstruction construction_;
const bool beside_;
bool stop = false;
bool drop_indexers = false; // see Release()
enum class TaskState {STARTING, IDLE, READY, RUNNING, COMPLETED, ERROR} state = TaskState::STARTING;
std::mutex m;
std::condition_variable c_running;
std::condition_variable c_start;
std::condition_variable c_done;
std::unique_ptr<IndexerResult> result = nullptr;
std::unique_ptr<TaskInput> task_input = nullptr;
std::thread worker_thread;
void Worker(int threadid);
public:
IndexerThread(const IndexingSettings& settings, int threadid, IndexerConstruction construction, bool beside);
~IndexerThread();
std::unique_ptr<IndexerResult> Run(const DiffractionExperiment &experiment, const std::vector<Coord> &recip,
bool severity_only = false);
// The thread drops the indexers it has built - once the frame it is on, if any, is done - and builds
// them again on the next frame that needs one. Returns when they are gone.
void Release();
void Finalize();
};
class IndexerThreadPool {
std::mutex m;
std::condition_variable c;
std::vector<uint8_t> worker_busy;
size_t worker_free_count;
std::vector<std::unique_ptr<IndexerThread>> tasks;
const int64_t viable_cell_min_spots;
const bool blocking;
const IndexingSettings settings_;
int GetFreeWorker();
public:
// beside: the pool serves a probe pass that holds GPUWorkBeside, so an FFT indexer that does not fit
// the card waits for the main line's image pass to end, not for the probes - it is one of them (see
// MakeFFTIndexerGPU).
IndexerThreadPool(const IndexingSettings& settings,
IndexerConstruction construction = IndexerConstruction::Preconstruct,
bool beside = false);
// The settings the pool's indexers were built with.
[[nodiscard]] const IndexingSettings &Settings() const { return settings_; }
// severity_only skips indexing and produces just the spindle severity - see Indexer::Run.
IndexerResult Run(const DiffractionExperiment& experiment, const std::vector<Coord>& recip,
bool severity_only = false);
// Give back to the card the device memory of the indexers built so far - an FFT indexer holds
// 0.6-1.2 GB of it - for a stretch with nothing to index. A frame that comes after all builds its
// indexer again, as on first use, and the indexer it gets computes what the dropped one would.
void ReleaseIndexers();
};