Jungfraujoch/tests/CudaHandledErrorTest.cpp

// SPDX-FileCopyrightText: 2026 Filip Leonarski, Paul Scherrer Institute
// SPDX-License-Identifier: GPL-3.0-only

#include <catch2/catch_all.hpp>
#include "../common/CUDAWrapper.h"

#ifdef JFJOCH_USE_CUDA

#include <cuda_runtime.h>
#include <limits>

#include "../common/AzimuthalIntegrationMapping.h"
#include "../common/AzimuthalIntegrationProfile.h"
#include "../common/DiffractionExperiment.h"
#include "../common/PixelMask.h"
#include "../compression/JFJochCompressor.h"
#include "../image_analysis/IndexAndRefine.h"
#include "../image_analysis/MXAnalysisWithoutFPGA.h"
#include "../image_analysis/indexing/CUDAMemHelpers.h"

// What makes a handled CUDA failure dangerous: the failed call leaves the error behind as the
// thread's last error, and nothing but cudaGetLastError() takes it away - later successful calls
// neither clear it nor return it. So a route that failed, was caught and was replaced by another
// one hands its error to the next cudaGetLastError() in the code that followed, which is the check
// after a kernel launch. That is how a broker logged a raw "out of memory" over an image whose
// buffers were all allocated. cuda_clear_error() is what a handled failure discharges it with.
TEST_CASE("CudaDevicePtr_FailedAllocationLeavesErrorUntilCleared", "[CUDAMemHelpers]") {
    if (get_gpu_count() == 0)
        SKIP("No CUDA GPU present");

    cuda_clear_error();
    REQUIRE_THROWS(CudaDevicePtr<uint8_t>(std::numeric_limits<size_t>::max(), CudaAlloc::Synchronous));

    // Work that goes fine in between changes nothing: the error is still waiting.
    CudaDevicePtr<uint8_t> fine(1 << 16);
    REQUIRE(cudaStreamSynchronize(cuda_allocation_stream()) == cudaSuccess);

    cuda_clear_error();
    CHECK(cudaGetLastError() == cudaSuccess);
}

// The device decoder is allowed to fail - the host decompresses instead - but the host route runs
// kernels of its own and checks cudaGetLastError() after them. An image must come out of that
// whole, and with nothing left behind for the next one.
TEST_CASE("MXAnalysis_HandledDeviceDecodeFailureLeavesNoError", "[CUDAMemHelpers]") {
    if (get_gpu_count() == 0)
        SKIP("No CUDA GPU present");

    constexpr size_t width = 1030, height = 1064;

    DiffractionExperiment experiment(DetDECTRIS(width, height, "Test", {}));
    experiment.ImagesPerTrigger(1).NumTriggers(1).PixelSigned(false)
            .DetectorDistance_mm(75).BeamX_pxl(515).BeamY_pxl(532).IncidentEnergy_keV(12.4);

    PixelMask pixel_mask(experiment);
    AzimuthalIntegrationMapping mapping(experiment, pixel_mask);
    IndexAndRefine index_and_refine(experiment, nullptr);
    MXAnalysisWithoutFPGA analysis(experiment, mapping, pixel_mask, index_and_refine);

    std::vector<uint16_t> pixels(width * height, 0);
    for (size_t i = 0; i < pixels.size(); i += 997)
        pixels[i] = 500;
    JFJochBitShuffleCompressor compressor(CompressionAlgorithm::BSHUF_LZ4);
    const std::vector<uint8_t> compressed = compressor.Compress(pixels);
    REQUIRE(!compressed.empty());

    DataMessage message{};
    message.number = 0;
    message.image = CompressedImage(compressed.data(), compressed.size(), width, height,
                                    CompressedImageMode::Uint16, CompressionAlgorithm::BSHUF_LZ4);

    SpotFindingSettings settings = DiffractionExperiment::DefaultDataProcessingSettings();
    settings.enable = false;

    // Stage the device route into failing, by leaving behind the error a request the card cannot
    // serve leaves.
    void *unservable = nullptr;
    REQUIRE(cudaMalloc(&unservable, std::numeric_limits<size_t>::max()) != cudaSuccess);

    AzimuthalIntegrationProfile profile(mapping);
    REQUIRE_NOTHROW(analysis.Analyze(message, profile, settings));
    CHECK(cudaGetLastError() == cudaSuccess);
}

#endif