cuFFT ships its transforms as PTX for every card (cuFFT 11 and 12 alike), so each plan has the driver compile kernels, and a second plan of the same shape compiles them again. From the driver's JIT cache that costs ~0.5 ms a plan; without it 45-130 ms, under cuFFT's process-wide lock - which, over the ~100 plans of molecular replacement, matches the stage pattern of the slow MR in the production broker. The cache is unusable in more ways than CUDA_CACHE_DISABLE: with no HOME at all (a systemd system service without User= gets none, and the driver does not fall back to the passwd entry), on a read-only or unwritable directory, on a filesystem whose fcntl locks fail (NFS without locking) - each measured as slow as no cache - or on a slow network filesystem (each plan opens and locks the cache ~10 times). - common/CudaJitCache: the path the driver uses (CUDA_CACHE_PATH, else $HOME/.nv/ComputeCache), its filesystem type, whether it is writable, whether its index opens read-write and takes the driver's fcntl read lock, CUDA_CACHE_DISABLE and a CUDA_CACHE_MAXSIZE below 64 MiB. One line: info when fine, a warning with the cause and the remedy (CUDA_CACHE_PATH on a local disk) when not, or when a plan takes over 10 ms. - WarmUpCuFFT returns the fastest of three 64^3 R2C plan makes after a first one that pays the initialisation (and a cold-cache compile): ~2 ms in all with a cache, ~0.3 s without. - jfjoch_broker runs it after its version line (0.15 s at start, cuFFT init and card 0's context included); rugnux on its existing background warm-up thread. - CUDAMemHelpers.h: the modules are PTX on every platform, not only on Windows. No result changes. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01PXc1zD1yxHqaR1DGdCTHL4
144 lines
6.6 KiB
C++
144 lines
6.6 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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#pragma once
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#include <thread>
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#include <mutex>
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#include <condition_variable>
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#include <queue>
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#include <functional>
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#include <future>
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#include <vector>
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#include <optional>
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#include <memory>
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#include <latch>
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#include "../common/JFJochMessages.h"
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#include "../common/DiffractionSpot.h"
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#include "../common/DiffractionExperiment.h"
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#include "Indexer.h"
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// When a worker builds its indexers.
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//
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// Preconstruct (the default, and what the online service needs): every indexer the requested
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// algorithm could resolve to is built while the pool is being constructed, so it is resident and
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// planned before the first frame arrives. Building one means a cuFFT plan plus ~0.6 GB of device
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// allocation, and the first cuFFT call in a process also pays the library's one-time init (0.3 s
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// measured); jfjoch_broker cannot have any of that land on the live data path, so holding an indexer
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// the resolved algorithm may never dispatch to is an accepted cost there.
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//
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// OnFirstUse (offline batch - rugnux, jfjoch_viewer): nothing is latency-critical, so the indexer is
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// built on the first frame that needs it. The algorithm is only resolved from the frame's
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// DiffractionExperiment (rotation -> FFT, stills with a known cell -> FFBIDX), so preconstructing
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// leaves each worker holding a fully allocated FFTIndexerGPU - 0.6 GB of cuFFT plan and histograms -
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// that can never be dispatched to.
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enum class IndexerConstruction { Preconstruct, OnFirstUse };
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// Force cuFFT's one-time library initialisation - 0.3 s measured, paid by whichever call happens to
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// be first - so it can be got out of the way on a background thread at startup rather than landing in
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// the middle of the first pass with nothing overlapping it. Returns how long a 3D plan takes to make
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// after that, in ms - about 1 from a working CUDA JIT cache, 60 or more without (see CudaJitCache.h) -
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// and NaN without a GPU.
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double WarmUpCuFFT();
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// cuFFT plans are kept and reused for as long as one of these lives, and destroyed when the last one
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// ends (CudaFFTPlanScope): one per processing run in `rugnux`, so no plan outlives the run that made it;
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// one for its lifetime in jfjoch_broker. Nothing without CUDA.
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class CudaFFTPlanScope;
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class FFTPlanReuse {
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std::unique_ptr<CudaFFTPlanScope> scope;
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public:
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FFTPlanReuse();
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~FFTPlanReuse();
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FFTPlanReuse(const FFTPlanReuse &) = delete;
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FFTPlanReuse &operator=(const FFTPlanReuse &) = delete;
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};
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// GPU FFT indexers are kept for reuse while one of these is alive, by card and the settings they are
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// built from, and destroyed when the last one ends. A pool's worker then borrows a kept indexer instead
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// of building one, and gives it back - not to the card - when it ends or is released (ReleaseIndexers):
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// the device memory stays taken in between. For jfjoch_broker's rugnux live runs, which build the same
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// pools for every pass of every collection; an indexer computes the same with any earlier frames behind
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// it, as it does within a pool. Nothing without CUDA.
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class FFTIndexerReuse {
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public:
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FFTIndexerReuse();
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~FFTIndexerReuse();
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FFTIndexerReuse(const FFTIndexerReuse &) = delete;
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FFTIndexerReuse &operator=(const FFTIndexerReuse &) = delete;
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};
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// Builds `count` GPU FFT indexers of these settings on the current card at the same time, and keeps them
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// for the pools that ask for them later (inside an FFTIndexerReuse; outside one they are only built and
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// destroyed). Nothing without a GPU.
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void KeepFFTIndexers(const IndexingSettings &settings, int count);
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class IndexerThread {
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struct TaskInput {
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const DiffractionExperiment &experiment;
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const std::vector<Coord> &recip;
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const bool severity_only;
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};
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// Held by value: with IndexerConstruction::OnFirstUse the worker builds its indexer long after
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// the constructor returned, and pools are routinely built from a temporary - for instance
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// IndexerThreadPool(experiment.GetIndexingSettings()), which returns by value.
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const IndexingSettings settings_;
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const IndexerConstruction construction_;
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const bool beside_;
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bool stop = false;
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bool drop_indexers = false; // see Release()
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enum class TaskState {STARTING, IDLE, READY, RUNNING, COMPLETED, ERROR} state = TaskState::STARTING;
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std::mutex m;
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std::condition_variable c_running;
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std::condition_variable c_start;
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std::condition_variable c_done;
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std::unique_ptr<IndexerResult> result = nullptr;
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std::unique_ptr<TaskInput> task_input = nullptr;
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std::thread worker_thread;
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void Worker(int threadid);
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public:
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IndexerThread(const IndexingSettings& settings, int threadid, IndexerConstruction construction, bool beside);
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~IndexerThread();
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std::unique_ptr<IndexerResult> Run(const DiffractionExperiment &experiment, const std::vector<Coord> &recip,
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bool severity_only = false);
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// The thread drops the indexers it has built - once the frame it is on, if any, is done - and builds
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// them again on the next frame that needs one. Returns when they are gone.
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void Release();
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void Finalize();
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};
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class IndexerThreadPool {
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std::mutex m;
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std::condition_variable c;
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std::vector<uint8_t> worker_busy;
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size_t worker_free_count;
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std::vector<std::unique_ptr<IndexerThread>> tasks;
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const int64_t viable_cell_min_spots;
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const bool blocking;
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const IndexingSettings settings_;
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int GetFreeWorker();
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public:
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// beside: the pool serves a probe pass that holds GPUWorkBeside, so an FFT indexer that does not fit
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// the card waits for the main line's image pass to end, not for the probes - it is one of them (see
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// MakeFFTIndexerGPU).
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IndexerThreadPool(const IndexingSettings& settings,
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IndexerConstruction construction = IndexerConstruction::Preconstruct,
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bool beside = false);
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// The settings the pool's indexers were built with.
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[[nodiscard]] const IndexingSettings &Settings() const { return settings_; }
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// severity_only skips indexing and produces just the spindle severity - see Indexer::Run.
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IndexerResult Run(const DiffractionExperiment& experiment, const std::vector<Coord>& recip,
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bool severity_only = false);
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// Give back to the card the device memory of the indexers built so far - an FFT indexer holds
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// 0.6-1.2 GB of it - for a stretch with nothing to index. A frame that comes after all builds its
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// indexer again, as on first use, and the indexer it gets computes what the dropped one would.
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void ReleaseIndexers();
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};
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