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Jungfraujoch/image_analysis/geom_refinement/BeamCenterBackgroundGPU.cu
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leonarski_fandClaude Opus 5.5 672e182d6a GPU engines wait for their stream before their buffers go; a lost context fails where it is seen
A pooled CudaDevicePtr frees on the thread's allocation stream, not on the engine's stream, and the
pool may hand the memory to another engine - or, past its release threshold, unmap it - as soon as
that free is reached, which on an idle allocation stream is at once. An engine destroyed with work
still queued (FFTIndexerGPU after SearchCap's last DirectionsChanged upload, a spot finder between
DetectAt and Extract, a shadow accumulator after a pending fold, any engine on an exception path)
thus had kernels or copies writing memory that was someone else's or no longer mapped. Now:
- CudaStream synchronises before cudaStreamDestroy (destructor and move-assignment), which covers
  engines whose own stream is declared after their buffers (FFTIndexerGPU, the gather buffer);
- every engine holding pooled buffers and a stream (shared or own, declared before the buffers)
  synchronises it in its destructor; BraggIntegrationEngineGPU also before EnsureCapacity
  reallocates, where a Run that threw leaves work queued.

A GPU failure that is handled no longer hides a lost context: ShadowFinder, BeamCenterFFT, the
rigid-body pool and model validation call cuda_throw_if_context_lost() before cuda_clear_error(),
as the device-decode fallbacks already did; RotationScaleMergeGPU's Alloc does so before waiting up
to ten minutes for GPU work beside it and then reporting a lost device as out of memory; and a
failed cudaMalloc says why. BeamCenterFFT logs the failure it used to drop silently, the
speculative geometry probe logs the exception it swallowed (its GPU fault was otherwise reported by
the merge beside it, under the merge's name), and RotationScaleMergeGPU's DeviceGuard no longer
throws from its destructor.

Only synchronisation and error paths change: p.hkl md5 and the MTZ data (gemmi) are identical to
the b530c2d full battery on myob_x10sa, cytc_x10sa, 8a1a, 9gdj, 11if, kdp_x10sa_20keV and 6z9g.

Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01SVmAWnzCmRKAXVUCdc4iNi
2026-10-10 10:59:24 +02:00

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// SPDX-FileCopyrightText: 2026 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
// SPDX-License-Identifier: GPL-3.0-only
#include "BeamCenterBackgroundGPU.h"
#include <cub/device/device_radix_sort.cuh>
#include "../indexing/CUDAMemHelpers.h"
namespace {
constexpr int THREADS = 256;
void check(cudaError_t err, const char *what) {
if (err != cudaSuccess)
throw JFJochException(JFJochExceptionCategory::GPUCUDAError,
std::string("Beam centre from background: ") + what + ": " + cudaGetErrorString(err));
}
// Every pixel's cell (BackgroundBand::CELLS where it is outside the band or unusable), its index,
// and its derivatives.
__global__ void bin_kernel(BackgroundBand band, int width, size_t npixels, float beam_x, float beam_y,
const char *__restrict__ usable, int32_t *__restrict__ key,
int32_t *__restrict__ index, float *__restrict__ jac_x,
float *__restrict__ jac_y) {
const size_t i = blockIdx.x * static_cast<size_t>(blockDim.x) + threadIdx.x;
if (i >= npixels)
return;
int cell = BackgroundBand::CELLS;
float jx = 0.0f, jy = 0.0f;
if (usable[i]) {
const int c = BackgroundBandCell(band, static_cast<int>(i % width), static_cast<int>(i / width),
beam_x, beam_y, jx, jy);
if (c >= 0)
cell = c;
}
key[i] = cell;
index[i] = static_cast<int32_t>(i);
jac_x[i] = jx;
jac_y[i] = jy;
}
// Where each cell's pixels start in the sorted keys; offset[CELLS] is the number of binned pixels.
__global__ void offset_kernel(const int32_t *__restrict__ sorted_key, size_t n, int32_t *__restrict__ offset) {
const int c = blockIdx.x * blockDim.x + threadIdx.x;
if (c > BackgroundBand::CELLS)
return;
size_t lo = 0, hi = n;
while (lo < hi) {
const size_t mid = (lo + hi) / 2;
if (sorted_key[mid] < c) lo = mid + 1;
else hi = mid;
}
offset[c] = static_cast<int32_t>(lo);
}
// One thread per cell, walking its pixels in pixel order: a partial sum per host row block, added to
// the cell's total when the block changes - the host's arithmetic, step for step. A cell whose pixels
// are clipped (clip_limit != nullptr) skips the ones above its limit, as the host's clip rounds do.
__global__ void sum_kernel(int width, const int32_t *__restrict__ offset, const int32_t *__restrict__ index,
const int32_t *__restrict__ row_block, const float *__restrict__ mean,
const float *__restrict__ jac_x, const float *__restrict__ jac_y,
const float *__restrict__ clip_limit,
double *__restrict__ sum, double *__restrict__ sum_sq,
double *__restrict__ sum_jx, double *__restrict__ sum_jy,
int32_t *__restrict__ count) {
const int c = blockIdx.x * blockDim.x + threadIdx.x;
if (c >= BackgroundBand::CELLS)
return;
const bool clipped = clip_limit != nullptr;
const float limit = clipped ? clip_limit[c] : 0.0f;
double s = 0, ss = 0, jx = 0, jy = 0;
double bs = 0, bss = 0, bjx = 0, bjy = 0;
int32_t n = 0;
int block = -1;
for (int32_t p = offset[c]; p < offset[c + 1]; p++) {
const int32_t i = index[p];
const float value = mean[i];
if (clipped && (limit < 0.0f || value > limit))
continue;
const int b = row_block[i / width];
if (b != block) {
s += bs; ss += bss; jx += bjx; jy += bjy;
bs = bss = bjx = bjy = 0;
block = b;
}
n++;
bs += value;
bss += static_cast<double>(value) * value;
if (!clipped) {
bjx += jac_x[i];
bjy += jac_y[i];
}
}
s += bs; ss += bss; jx += bjx; jy += bjy;
sum[c] = s;
sum_sq[c] = ss;
count[c] = n;
if (!clipped) {
sum_jx[c] = jx;
sum_jy[c] = jy;
}
}
} // namespace
struct BeamCenterBackgroundGPU::Impl {
int width, height;
size_t npixels;
CudaStream stream;
CudaDevicePtr<char> usable;
CudaDevicePtr<float> mean;
CudaDevicePtr<int32_t> row_block;
CudaDevicePtr<int32_t> key, sorted_key, index, sorted_index;
CudaDevicePtr<float> jac_x, jac_y;
CudaDevicePtr<int32_t> offset;
CudaDevicePtr<float> clip_limit;
CudaDevicePtr<double> sum, sum_sq, sum_jx, sum_jy;
CudaDevicePtr<int32_t> count;
CudaDevicePtr<uint8_t> sort_scratch;
size_t sort_scratch_bytes = 0;
// Waits for the stream, which is destroyed after the buffers freed before it (see CudaDevicePtr).
~Impl() { cudaStreamSynchronize(stream); }
Impl(int w, int h)
: width(w), height(h), npixels(static_cast<size_t>(w) * h),
usable(npixels), mean(npixels), row_block(h),
key(npixels), sorted_key(npixels), index(npixels), sorted_index(npixels),
jac_x(npixels), jac_y(npixels), offset(BackgroundBand::CELLS + 1),
clip_limit(BackgroundBand::CELLS),
sum(BackgroundBand::CELLS), sum_sq(BackgroundBand::CELLS),
sum_jx(BackgroundBand::CELLS), sum_jy(BackgroundBand::CELLS),
count(BackgroundBand::CELLS) {
// Keys run to CELLS inclusive, the bin of everything outside the band.
check(cub::DeviceRadixSort::SortPairs(nullptr, sort_scratch_bytes, key.get(), sorted_key.get(),
index.get(), sorted_index.get(), npixels, 0, end_bit(), stream),
"sort size");
sort_scratch = CudaDevicePtr<uint8_t>(sort_scratch_bytes);
}
static int end_bit() {
int bits = 0;
while ((1 << bits) <= BackgroundBand::CELLS) bits++;
return bits;
}
void Download(std::vector<double> &s, std::vector<double> &ss, std::vector<double> *jx,
std::vector<double> *jy, std::vector<int32_t> &n) {
const size_t cells = BackgroundBand::CELLS;
check(cudaMemcpyAsync(s.data(), sum.get(), cells * sizeof(double), cudaMemcpyDeviceToHost, stream), "copy");
check(cudaMemcpyAsync(ss.data(), sum_sq.get(), cells * sizeof(double), cudaMemcpyDeviceToHost, stream), "copy");
if (jx) check(cudaMemcpyAsync(jx->data(), sum_jx.get(), cells * sizeof(double), cudaMemcpyDeviceToHost, stream), "copy");
if (jy) check(cudaMemcpyAsync(jy->data(), sum_jy.get(), cells * sizeof(double), cudaMemcpyDeviceToHost, stream), "copy");
check(cudaMemcpyAsync(n.data(), count.get(), cells * sizeof(int32_t), cudaMemcpyDeviceToHost, stream), "copy");
check(cudaStreamSynchronize(stream), "sums");
}
};
BeamCenterBackgroundGPU::BeamCenterBackgroundGPU(int width, int height, const std::vector<int> &block_row,
const char *usable, const float *mean)
: impl(std::make_unique<Impl>(width, height)) {
std::vector<int32_t> row_block(height);
for (size_t b = 0; b + 1 < block_row.size(); b++)
for (int y = block_row[b]; y < block_row[b + 1]; y++)
row_block[y] = static_cast<int32_t>(b);
check(cudaMemcpyAsync(impl->row_block.get(), row_block.data(), height * sizeof(int32_t),
cudaMemcpyHostToDevice, impl->stream), "upload");
check(cudaMemcpyAsync(impl->usable.get(), usable, impl->npixels, cudaMemcpyHostToDevice, impl->stream), "upload");
check(cudaMemcpyAsync(impl->mean.get(), mean, impl->npixels * sizeof(float), cudaMemcpyHostToDevice,
impl->stream), "upload");
check(cudaStreamSynchronize(impl->stream), "upload");
}
BeamCenterBackgroundGPU::~BeamCenterBackgroundGPU() = default;
void BeamCenterBackgroundGPU::Bin(const BackgroundBand &band, float beam_x, float beam_y,
std::vector<double> &sum, std::vector<double> &sum_sq,
std::vector<double> &sum_jx, std::vector<double> &sum_jy,
std::vector<int32_t> &count) {
Impl &d = *impl;
const auto blocks = static_cast<unsigned>((d.npixels + THREADS - 1) / THREADS);
bin_kernel<<<blocks, THREADS, 0, d.stream>>>(band, d.width, d.npixels, beam_x, beam_y, d.usable,
d.key, d.index, d.jac_x, d.jac_y);
check(cudaGetLastError(), "bin");
// A radix sort is stable, so each cell's pixels come out in pixel order.
check(cub::DeviceRadixSort::SortPairs(d.sort_scratch.get(), d.sort_scratch_bytes, d.key.get(),
d.sorted_key.get(), d.index.get(), d.sorted_index.get(),
d.npixels, 0, Impl::end_bit(), d.stream), "sort");
constexpr int cell_blocks = (BackgroundBand::CELLS + 1 + THREADS - 1) / THREADS;
offset_kernel<<<cell_blocks, THREADS, 0, d.stream>>>(d.sorted_key, d.npixels, d.offset);
check(cudaGetLastError(), "offsets");
sum_kernel<<<cell_blocks, THREADS, 0, d.stream>>>(d.width, d.offset, d.sorted_index, d.row_block, d.mean,
d.jac_x, d.jac_y, nullptr, d.sum, d.sum_sq,
d.sum_jx, d.sum_jy, d.count);
check(cudaGetLastError(), "sums");
d.Download(sum, sum_sq, &sum_jx, &sum_jy, count);
}
void BeamCenterBackgroundGPU::Clip(const std::vector<float> &clip_limit,
std::vector<double> &sum, std::vector<double> &sum_sq,
std::vector<int32_t> &count) {
Impl &d = *impl;
check(cudaMemcpyAsync(d.clip_limit.get(), clip_limit.data(), BackgroundBand::CELLS * sizeof(float),
cudaMemcpyHostToDevice, d.stream), "upload");
constexpr int cell_blocks = (BackgroundBand::CELLS + THREADS - 1) / THREADS;
sum_kernel<<<cell_blocks, THREADS, 0, d.stream>>>(d.width, d.offset, d.sorted_index, d.row_block, d.mean,
d.jac_x, d.jac_y, d.clip_limit, d.sum, d.sum_sq,
d.sum_jx, d.sum_jy, d.count);
check(cudaGetLastError(), "clip");
d.Download(sum, sum_sq, nullptr, nullptr, count);
}