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Jungfraujoch/image_analysis/bragg_integration/BraggPredictionGPU.cu
2025-10-23 09:05:11 +02:00

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// SPDX-FileCopyrightText: 2025 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
// SPDX-License-Identifier: GPL-3.0-only
#include "BraggPredictionGPU.h"
#ifdef JFJOCH_USE_CUDA
#include "../indexing/CUDAMemHelpers.h"
#include <cuda_runtime.h>
namespace {
__device__ inline bool is_odd(int v) { return (v & 1) != 0; }
__device__ inline bool compute_reflection(const KernelConsts &C, int h, int k, int l, Reflection &out) {
if (h == 0 && k == 0 && l == 0)
return false;
// Systematic absences (centering only)
// P, I, A, B, C, F supported
switch (C.centering) {
case 'I':
if (is_odd(h + k + l))
return false;
break;
case 'A':
if (is_odd(k + l))
return false;
break;
case 'B':
if (is_odd(h + l))
return false;
break;
case 'C':
if (is_odd(h + k))
return false;
break;
case 'F':
if ((is_odd(h + k)) || (is_odd(h + l)) || (is_odd(k + l)))
return false;
break;
case 'R': {
// Rhombohedral in hexagonal setting (hR, a_h=b_h, gamma=120°):
// Condition: -h + k + l = 3n
int mod = (-h + k + l) % 3;
if (mod < 0) mod += 3;
if (mod != 0) return false;
break;
}
default:
break;
}
float Ah_x = C.Astar.x * h;
float Ah_y = C.Astar.y * h;
float Ah_z = C.Astar.z * h;
float AhBk_x = Ah_x + C.Bstar.x * k;
float AhBk_y = Ah_y + C.Bstar.y * k;
float AhBk_z = Ah_z + C.Bstar.z * k;
float rx = AhBk_x + C.Cstar.x * l;
float ry = AhBk_y + C.Cstar.y * l;
float rz = AhBk_z + C.Cstar.z * l;
float dot = rx * rx + ry * ry + rz * rz;
if (dot > C.one_over_dmax_sq) return false;
float Sx = rx + C.S0.x;
float Sy = ry + C.S0.y;
float Sz = rz + C.S0.z;
float S_len = sqrtf(Sx * Sx + Sy * Sy + Sz * Sz);
float dist_ewald = fabsf(S_len - C.one_over_wavelength);
if (dist_ewald > C.ewald_cutoff) return false;
float Srx = C.rot[0] * Sx + C.rot[1] * Sy + C.rot[2] * Sz;
float Sry = C.rot[3] * Sx + C.rot[4] * Sy + C.rot[5] * Sz;
float Srz = C.rot[6] * Sx + C.rot[7] * Sy + C.rot[8] * Sz;
if (Srz <= 0.0f) return false;
float coeff = C.coeff_const / Srz;
float x = C.beam_x + Srx * coeff;
float y = C.beam_y + Sry * coeff;
if (x < 0.0f || x >= C.det_width_pxl || y < 0.0f || y >= C.det_height_pxl) return false;
out.h = h;
out.k = k;
out.l = l;
out.predicted_x = x;
out.predicted_y = y;
out.d = 1.0f / sqrtf(dot);
out.dist_ewald = dist_ewald;
return true;
}
__global__ void bragg_kernel_3d(const KernelConsts *__restrict__ kc,
int max_hkl,
int max_reflections,
Reflection *__restrict__ out,
int *__restrict__ counter) {
int range = 2 * max_hkl;
int hi = blockIdx.x * blockDim.x + threadIdx.x;
int ki = blockIdx.y * blockDim.y + threadIdx.y;
int li = blockIdx.z * blockDim.z + threadIdx.z;
if (hi >= range || ki >= range || li >= range) return;
int h = hi - max_hkl;
int k = ki - max_hkl;
int l = li - max_hkl;
Reflection r{};
if (!compute_reflection(*kc, h, k, l, r)) return;
int pos = atomicAdd(counter, 1);
if (pos < max_reflections) out[pos] = r;
else atomicSub(counter, 1);
}
inline KernelConsts BuildKernelConsts(const DiffractionExperiment &experiment,
const CrystalLattice &lattice,
float high_res_A,
float ewald_dist_cutoff,
char centering) {
KernelConsts kc{};
auto geom = experiment.GetDiffractionGeometry();
kc.det_width_pxl = static_cast<float>(experiment.GetXPixelsNum());
kc.det_height_pxl = static_cast<float>(experiment.GetYPixelsNum());
kc.beam_x = geom.GetBeamX_pxl();
kc.beam_y = geom.GetBeamY_pxl();
kc.coeff_const = geom.GetDetectorDistance_mm() / geom.GetPixelSize_mm();
float one_over_dmax = 1.0f / high_res_A;
kc.one_over_dmax_sq = one_over_dmax * one_over_dmax;
kc.one_over_wavelength = 1.0f / geom.GetWavelength_A();
kc.ewald_cutoff = ewald_dist_cutoff;
kc.Astar = lattice.Astar();
kc.Bstar = lattice.Bstar();
kc.Cstar = lattice.Cstar();
kc.S0 = geom.GetScatteringVector();
kc.centering = centering;
auto rotT = geom.GetPoniRotMatrix().transpose().arr();
for (int i = 0; i < 9; ++i) kc.rot[i] = rotT[i];
return kc;
}
} // namespace
BraggPredictionGPU::BraggPredictionGPU(int max_reflections)
: BraggPrediction(max_reflections),
reg_out(reflections), d_out(max_reflections),
dK(1), d_count(1), h_count(1) {
}
int BraggPredictionGPU::Calc(const DiffractionExperiment &experiment,
const CrystalLattice &lattice,
const BraggPredictionSettings &settings) {
// Build constants on host
KernelConsts hK = BuildKernelConsts(experiment, lattice, settings.high_res_A, settings.ewald_dist_cutoff, settings.centering);
cudaMemcpyAsync(dK, &hK, sizeof(KernelConsts), cudaMemcpyHostToDevice, stream);
cudaMemsetAsync(d_count, 0, sizeof(int), stream);
// Configure and launch on the stream
const int range = 2 * settings.max_hkl;
dim3 block(8, 8, 8);
dim3 grid((range + block.x - 1) / block.x,
(range + block.y - 1) / block.y,
(range + block.z - 1) / block.z);
bragg_kernel_3d<<<grid, block, 0, stream>>>(dK, settings.max_hkl, max_reflections, d_out, d_count);
// Async D2H count and synchronize
cudaMemcpyAsync(h_count, d_count, sizeof(int), cudaMemcpyDeviceToHost, stream);
cudaStreamSynchronize(stream);
int count = *h_count.get();
if (count > max_reflections) count = max_reflections;
if (count == 0)
return {};
cudaMemcpyAsync(reflections.data(), d_out, sizeof(Reflection) * count, cudaMemcpyDeviceToHost, stream);
cudaStreamSynchronize(stream);
return count;
}
#endif