The two pre-scan steps that were still CPU-bound in a GPU build now run where the projection already is. - FindBeamCenterFromBackground: the per-iteration binning pass and the two clip rounds run on the device (BeamCenterBackgroundGPU); the fit itself stays on the host. Each cell is summed in the host's order (pixel order within the host's row blocks, blocks in order), and the per-pixel cell/derivative formula is shared (BackgroundBand.h). The angles come from BackgroundAtan2 (IEEE ops only) instead of atan2f, and both translation units are compiled without FMA contraction, so host and device give the same bits: 0 of 6.5 M pixels in a different cell, identical walks on the three in-house rotation sets. With glibc/CUDA atan2f and default contraction ~30 pixels per 16 Mpx sweep changed cell and the fitted centre moved by up to 0.05 px. - ShadowFinder::GetMask: the whole mask (pooling, ring medians, components, morphology, hole fill, arm search) runs on the device from ShadowAccumulatorGPU's projection (ShadowMaskGPU), so the 360 MB projection no longer comes back; the mean projection is divided on the device too (same bits). The two small fits over rings and sectors (BlockedOutTo, HarmonicFit) are shared with the host path in ShadowFinderInternal.h. Integers, comparisons, sorts and components are exact; the polarization trig, the Poisson log and the arm-search azimuth are not, so a pixel at a threshold can differ. The one-time change against the previous CPU arithmetic (BackgroundAtan2, no contraction), measured on the myoglobin, cytochrome C and thaumatin rotation sets: ring centre moves 0.002-0.045 px (fit sigma 0.75-1.2 px), beam-centre capture 0.01-0.04 px; beam-stop mask differs on 31 / 144 / 53 pixels of 259k / 144k / 198k (25 of the myoglobin ones are GPU-vs-CPU arithmetic in the mask, the rest follow the centre); hot-pixel mask identical. Spot width, integration radii, bandwidth, beam-centre arbitration, indexing, space group, cell, resolution and the merged statistics table are identical; only the error model moves in its 4th digit. CPU build: the same centres and decisions. Timing (GPU, box at load 30-38): ring walk 0.54 -> 0.23-0.27 s, mask 1.24-1.44 -> 0.18-0.22 s, beam-centre capture walk 1.1-1.3 -> 0.31-0.35 s. Tests: ShadowFinder_DeviceMaskMatchesHost, BeamCenterFromBackground_DeviceMatchesHost (bit-exact), plus [ShadowFinder], [BeamCenter], [HotPixelFinder]. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01K5K8jvPPbmCrbqnWkddTuB
211 lines
9.9 KiB
Plaintext
211 lines
9.9 KiB
Plaintext
// SPDX-FileCopyrightText: 2026 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 "BeamCenterBackgroundGPU.h"
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#include <cub/device/device_radix_sort.cuh>
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#include "../indexing/CUDAMemHelpers.h"
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namespace {
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constexpr int THREADS = 256;
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void check(cudaError_t err, const char *what) {
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if (err != cudaSuccess)
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throw JFJochException(JFJochExceptionCategory::GPUCUDAError,
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std::string("Beam centre from background: ") + what + ": " + cudaGetErrorString(err));
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}
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// Every pixel's cell (BackgroundBand::CELLS where it is outside the band or unusable), its index,
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// and its derivatives.
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__global__ void bin_kernel(BackgroundBand band, int width, size_t npixels, float beam_x, float beam_y,
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const char *__restrict__ usable, int32_t *__restrict__ key,
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int32_t *__restrict__ index, float *__restrict__ jac_x,
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float *__restrict__ jac_y) {
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const size_t i = blockIdx.x * static_cast<size_t>(blockDim.x) + threadIdx.x;
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if (i >= npixels)
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return;
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int cell = BackgroundBand::CELLS;
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float jx = 0.0f, jy = 0.0f;
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if (usable[i]) {
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const int c = BackgroundBandCell(band, static_cast<int>(i % width), static_cast<int>(i / width),
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beam_x, beam_y, jx, jy);
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if (c >= 0)
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cell = c;
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}
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key[i] = cell;
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index[i] = static_cast<int32_t>(i);
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jac_x[i] = jx;
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jac_y[i] = jy;
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}
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// Where each cell's pixels start in the sorted keys; offset[CELLS] is the number of binned pixels.
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__global__ void offset_kernel(const int32_t *__restrict__ sorted_key, size_t n, int32_t *__restrict__ offset) {
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const int c = blockIdx.x * blockDim.x + threadIdx.x;
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if (c > BackgroundBand::CELLS)
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return;
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size_t lo = 0, hi = n;
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while (lo < hi) {
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const size_t mid = (lo + hi) / 2;
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if (sorted_key[mid] < c) lo = mid + 1;
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else hi = mid;
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}
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offset[c] = static_cast<int32_t>(lo);
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}
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// One thread per cell, walking its pixels in pixel order: a partial sum per host row block, added to
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// the cell's total when the block changes - the host's arithmetic, step for step. A cell whose pixels
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// are clipped (clip_limit != nullptr) skips the ones above its limit, as the host's clip rounds do.
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__global__ void sum_kernel(int width, const int32_t *__restrict__ offset, const int32_t *__restrict__ index,
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const int32_t *__restrict__ row_block, const float *__restrict__ mean,
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const float *__restrict__ jac_x, const float *__restrict__ jac_y,
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const float *__restrict__ clip_limit,
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double *__restrict__ sum, double *__restrict__ sum_sq,
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double *__restrict__ sum_jx, double *__restrict__ sum_jy,
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int32_t *__restrict__ count) {
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const int c = blockIdx.x * blockDim.x + threadIdx.x;
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if (c >= BackgroundBand::CELLS)
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return;
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const bool clipped = clip_limit != nullptr;
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const float limit = clipped ? clip_limit[c] : 0.0f;
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double s = 0, ss = 0, jx = 0, jy = 0;
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double bs = 0, bss = 0, bjx = 0, bjy = 0;
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int32_t n = 0;
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int block = -1;
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for (int32_t p = offset[c]; p < offset[c + 1]; p++) {
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const int32_t i = index[p];
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const float value = mean[i];
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if (clipped && (limit < 0.0f || value > limit))
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continue;
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const int b = row_block[i / width];
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if (b != block) {
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s += bs; ss += bss; jx += bjx; jy += bjy;
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bs = bss = bjx = bjy = 0;
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block = b;
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}
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n++;
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bs += value;
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bss += static_cast<double>(value) * value;
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if (!clipped) {
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bjx += jac_x[i];
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bjy += jac_y[i];
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}
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}
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s += bs; ss += bss; jx += bjx; jy += bjy;
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sum[c] = s;
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sum_sq[c] = ss;
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count[c] = n;
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if (!clipped) {
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sum_jx[c] = jx;
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sum_jy[c] = jy;
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}
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}
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} // namespace
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struct BeamCenterBackgroundGPU::Impl {
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int width, height;
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size_t npixels;
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CudaStream stream;
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CudaDevicePtr<char> usable;
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CudaDevicePtr<float> mean;
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CudaDevicePtr<int32_t> row_block;
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CudaDevicePtr<int32_t> key, sorted_key, index, sorted_index;
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CudaDevicePtr<float> jac_x, jac_y;
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CudaDevicePtr<int32_t> offset;
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CudaDevicePtr<float> clip_limit;
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CudaDevicePtr<double> sum, sum_sq, sum_jx, sum_jy;
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CudaDevicePtr<int32_t> count;
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CudaDevicePtr<uint8_t> sort_scratch;
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size_t sort_scratch_bytes = 0;
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Impl(int w, int h)
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: width(w), height(h), npixels(static_cast<size_t>(w) * h),
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usable(npixels), mean(npixels), row_block(h),
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key(npixels), sorted_key(npixels), index(npixels), sorted_index(npixels),
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jac_x(npixels), jac_y(npixels), offset(BackgroundBand::CELLS + 1),
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clip_limit(BackgroundBand::CELLS),
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sum(BackgroundBand::CELLS), sum_sq(BackgroundBand::CELLS),
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sum_jx(BackgroundBand::CELLS), sum_jy(BackgroundBand::CELLS),
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count(BackgroundBand::CELLS) {
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// Keys run to CELLS inclusive, the bin of everything outside the band.
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check(cub::DeviceRadixSort::SortPairs(nullptr, sort_scratch_bytes, key.get(), sorted_key.get(),
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index.get(), sorted_index.get(), npixels, 0, end_bit(), stream),
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"sort size");
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sort_scratch = CudaDevicePtr<uint8_t>(sort_scratch_bytes);
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}
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static int end_bit() {
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int bits = 0;
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while ((1 << bits) <= BackgroundBand::CELLS) bits++;
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return bits;
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}
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void Download(std::vector<double> &s, std::vector<double> &ss, std::vector<double> *jx,
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std::vector<double> *jy, std::vector<int32_t> &n) {
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const size_t cells = BackgroundBand::CELLS;
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check(cudaMemcpyAsync(s.data(), sum.get(), cells * sizeof(double), cudaMemcpyDeviceToHost, stream), "copy");
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check(cudaMemcpyAsync(ss.data(), sum_sq.get(), cells * sizeof(double), cudaMemcpyDeviceToHost, stream), "copy");
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if (jx) check(cudaMemcpyAsync(jx->data(), sum_jx.get(), cells * sizeof(double), cudaMemcpyDeviceToHost, stream), "copy");
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if (jy) check(cudaMemcpyAsync(jy->data(), sum_jy.get(), cells * sizeof(double), cudaMemcpyDeviceToHost, stream), "copy");
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check(cudaMemcpyAsync(n.data(), count.get(), cells * sizeof(int32_t), cudaMemcpyDeviceToHost, stream), "copy");
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check(cudaStreamSynchronize(stream), "sums");
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}
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};
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BeamCenterBackgroundGPU::BeamCenterBackgroundGPU(int width, int height, const std::vector<int> &block_row,
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const char *usable, const float *mean)
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: impl(std::make_unique<Impl>(width, height)) {
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std::vector<int32_t> row_block(height);
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for (size_t b = 0; b + 1 < block_row.size(); b++)
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for (int y = block_row[b]; y < block_row[b + 1]; y++)
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row_block[y] = static_cast<int32_t>(b);
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check(cudaMemcpyAsync(impl->row_block.get(), row_block.data(), height * sizeof(int32_t),
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cudaMemcpyHostToDevice, impl->stream), "upload");
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check(cudaMemcpyAsync(impl->usable.get(), usable, impl->npixels, cudaMemcpyHostToDevice, impl->stream), "upload");
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check(cudaMemcpyAsync(impl->mean.get(), mean, impl->npixels * sizeof(float), cudaMemcpyHostToDevice,
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impl->stream), "upload");
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check(cudaStreamSynchronize(impl->stream), "upload");
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}
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BeamCenterBackgroundGPU::~BeamCenterBackgroundGPU() = default;
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void BeamCenterBackgroundGPU::Bin(const BackgroundBand &band, float beam_x, float beam_y,
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std::vector<double> &sum, std::vector<double> &sum_sq,
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std::vector<double> &sum_jx, std::vector<double> &sum_jy,
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std::vector<int32_t> &count) {
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Impl &d = *impl;
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const auto blocks = static_cast<unsigned>((d.npixels + THREADS - 1) / THREADS);
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bin_kernel<<<blocks, THREADS, 0, d.stream>>>(band, d.width, d.npixels, beam_x, beam_y, d.usable,
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d.key, d.index, d.jac_x, d.jac_y);
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check(cudaGetLastError(), "bin");
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// A radix sort is stable, so each cell's pixels come out in pixel order.
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check(cub::DeviceRadixSort::SortPairs(d.sort_scratch.get(), d.sort_scratch_bytes, d.key.get(),
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d.sorted_key.get(), d.index.get(), d.sorted_index.get(),
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d.npixels, 0, Impl::end_bit(), d.stream), "sort");
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constexpr int cell_blocks = (BackgroundBand::CELLS + 1 + THREADS - 1) / THREADS;
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offset_kernel<<<cell_blocks, THREADS, 0, d.stream>>>(d.sorted_key, d.npixels, d.offset);
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check(cudaGetLastError(), "offsets");
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sum_kernel<<<cell_blocks, THREADS, 0, d.stream>>>(d.width, d.offset, d.sorted_index, d.row_block, d.mean,
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d.jac_x, d.jac_y, nullptr, d.sum, d.sum_sq,
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d.sum_jx, d.sum_jy, d.count);
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check(cudaGetLastError(), "sums");
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d.Download(sum, sum_sq, &sum_jx, &sum_jy, count);
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}
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void BeamCenterBackgroundGPU::Clip(const std::vector<float> &clip_limit,
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std::vector<double> &sum, std::vector<double> &sum_sq,
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std::vector<int32_t> &count) {
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Impl &d = *impl;
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check(cudaMemcpyAsync(d.clip_limit.get(), clip_limit.data(), BackgroundBand::CELLS * sizeof(float),
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cudaMemcpyHostToDevice, d.stream), "upload");
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constexpr int cell_blocks = (BackgroundBand::CELLS + THREADS - 1) / THREADS;
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sum_kernel<<<cell_blocks, THREADS, 0, d.stream>>>(d.width, d.offset, d.sorted_index, d.row_block, d.mean,
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d.jac_x, d.jac_y, d.clip_limit, d.sum, d.sum_sq,
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d.sum_jx, d.sum_jy, d.count);
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check(cudaGetLastError(), "clip");
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d.Download(sum, sum_sq, nullptr, nullptr, count);
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}
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