Files
leonarski_fandClaude Opus 5.5 b6392a3f58 RESULT-CHANGING (ulp level, CUDA builds): the CUDA model density is the CPU walk's, bit for bit
ModelDensityGPU's gather had arithmetic of its own: per-thread offsets in Cartesian, the atom's
nearest image to the brick, r2 = x x + y y + z z, the radius squared in float. It now does what
UseDensityBoxesByPlane + AtomDensity (ModelGrid.cpp) and ModelDensityMetal.metal do, in their order:
- each brick's atoms carry their box (c - d, wrapped start, 2 d); a point is in the box by a
  subtraction, and f = centre - (u, v, w) in the box's own unwrapped index;
- x = m00 fx + (m01 fy + m02 fz), y = m11 fy + m12 fz, z = m22 fz with gemmi's orth_n
  (orth * (1/n), as Grid sets it) in float; r2 = (y y + z z) + x x against max_r2 = float(r^2)
  rounded from the double radius (new ModelDensityAtom field);
- gemmi's expapprox, the five Gaussians in order, atoms in model order per point. Device code is
  already compiled with --fmad=false (top-level CMakeLists), so nothing is contracted.
- The centres are no longer wrapped into the cell (ModelStructureFactorsGPU, RigidBodyGPU's
  place_kernel): float(fractional * n), as MakeDensityBox holds them; the mask keeps wrapped
  fractional coordinates. The 'narrow' nearest-image branch is gone: Supports() already leaves
  only boxes narrower than the cell.
The target is PutModelDensityOnGrid() with no orbits to symmetrize (one copy of the content, which
is what the gather grids; symmetry stays composed in reciprocal space). A rounding tie in the box
centre c (float on the GPU, double on the CPU) changes no point: either box covers the sphere with
half a spacing to spare. New ModelDensityGPU_BitIdenticalToCPU ([ModelValidation][gpu]) memcmps the
grids: triclinic P1 and P 21 21 21 cells, 3000 atoms over -0.5..1.5 of the cell, a quarter
anisotropic - 0 points differ.

RTX 5080, alternating base (8d199cceb) / this, under the GPU lock:
- gather kernel (nsys): 4nwv --model median 2.06 -> 2.55 ms, total 0.79 -> 0.97 s;
  9s02 --mr median 0.30 -> 0.37 ms, total 0.94 -> 1.17 s (+~25%, the box test and per-point
  index arithmetic).
- wall, two each: 4nwv --model 76.0/68.9 -> 74.4/71.0 s, --mr 71.3/71.1 -> 70.9/71.6 s;
  9s02 --model 25.1/22.6 -> 23.3/23.5 s, --mr 23.3/23.6 -> 23.3/23.2 s; 5reo --model
  6.2/5.5 -> 5.5/5.7 s. Model validation 4nwv 12.4/12.3 -> 12.3/11.7 s; MR 4nwv 15.4/15.2 ->
  15.4/15.1 s, 9s02 2.3/2.4 -> 2.4/2.4 s: no change beyond noise.
- outputs (each build run-to-run identical): p.hkl identical on all; R-work/R-free and every
  decision unchanged (4nwv validation 0.2982/0.2969, 9s02 MR AGREES P 21 21 2 0.2503/0.2517,
  4nwv MR UNDECIDED I 2 2 2 / I 21 21 21). Moved: MODEL_FIT_SIGMA 9s02 99.21 -> 101.68, 5reo
  103.96 -> 104.98; MR placement Z 9s02 142.1 -> 145.6, 4nwv 46.7 -> 46.2; 4nwv anomalous site
  4.01 -> 4.02 sigma; 4nwv placed model 1322/125462 lines in the last digit (2fo-fc max |d| 0.04
  rms, CC 0.99999994); 9s02/5reo models identical, maps to 2e-5 rms.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01PXc1zD1yxHqaR1DGdCTHL4
2026-10-18 18:10:23 +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 "ModelDensityGPU.h"
#include <algorithm>
#include <cmath>
#include <cub/cub.cuh>
#include "../../common/JFJochException.h"
namespace {
void cuda_err(cudaError_t val) {
if (val != cudaSuccess)
throw JFJochException(JFJochExceptionCategory::GPUCUDAError, cudaGetErrorString(val));
}
constexpr int BRICK = 8; // the gather's bricks are BRICK^3 grid points, one block each
constexpr int GATHER_TILE = 128; // atoms staged in shared memory at a time
constexpr int MAX_BRICKS_PER_AXIS = 16; // an atom's box touches at most this many bricks along an axis
constexpr int THREADS = 256;
__device__ __forceinline__ int imod(int a, int n) {
const int r = a % n;
return r < 0 ? r + n : r;
}
// gemmi's unsafe_expapprox() (formfact.hpp), the exponential the density is computed with.
__device__ __forceinline__ float expapprox(float x) {
const float val = 12102203.1615614f * x + 1065353216.f;
const int vali = static_cast<int>(val);
const float a = __int_as_float(vali & 0x7F800000);
const float b = __int_as_float((vali & 0x7FFFFF) | 0x3F800000);
return a * (0.509871020f + b * (0.312146713f + b * (0.166617139f + b * (-2.190619930e-3f + b * 1.3555747234e-2f))));
}
// The distinct bricks the points c - d ... c + d of one axis fall in, wrapped into the cell. A grid size
// that is not a multiple of BRICK leaves the last brick partial, which is why this is done on wrapped
// points and not in brick coordinates. -1 where there are more than MAX_BRICKS_PER_AXIS of them.
__device__ int axis_bricks(int c, int d, int n, int *out) {
int k = 0;
for (int p = c - d; p <= c + d; p++) {
const int b = imod(p, n) / BRICK;
bool seen = false;
for (int j = 0; j < k; j++)
seen = seen || out[j] == b;
if (seen)
continue;
if (k == MAX_BRICKS_PER_AXIS)
return -1;
out[k++] = b;
}
return k;
}
// The bricks atom i's box touches, per axis. The box is gemmi's: `box` points either side of the
// point nearest the atom.
__device__ void atom_bricks(const float4 &pos, const int *box, int nu, int nv, int nw, int *bu, int &nbu, int *bv,
int &nbv, int *bw, int &nbw) {
nbu = axis_bricks(__float2int_rn(pos.x), box[0], nu, bu);
nbv = axis_bricks(__float2int_rn(pos.y), box[1], nv, bv);
nbw = axis_bricks(__float2int_rn(pos.z), box[2], nw, bw);
}
__global__ void count_pairs_kernel(const float4 *pos, const int *box, int n, int nu, int nv, int nw, int *count,
int *overflow) {
const int i = blockIdx.x * blockDim.x + threadIdx.x;
if (i > n)
return;
if (i == n) {
count[n] = 0; // so the exclusive scan's last entry is the total
return;
}
int bu[MAX_BRICKS_PER_AXIS], bv[MAX_BRICKS_PER_AXIS], bw[MAX_BRICKS_PER_AXIS], a, b, c;
atom_bricks(pos[i], box + 3 * i, nu, nv, nw, bu, a, bv, b, bw, c);
if (a < 0 || b < 0 || c < 0) {
*overflow = 1;
a = b = c = 0;
}
count[i] = a * b * c;
}
// The (brick, atom) pairs, atom-major: sorted stably by brick, each brick's atoms stay in model order.
__global__ void fill_pairs_kernel(const float4 *pos, const int *box, int n, int nu, int nv, int nw,
const int *offset, int *key, int *value) {
const int i = blockIdx.x * blockDim.x + threadIdx.x;
if (i >= n)
return;
int bu[MAX_BRICKS_PER_AXIS], bv[MAX_BRICKS_PER_AXIS], bw[MAX_BRICKS_PER_AXIS], a, b, c;
atom_bricks(pos[i], box + 3 * i, nu, nv, nw, bu, a, bv, b, bw, c);
const int nbu = (nu + BRICK - 1) / BRICK, nbv = (nv + BRICK - 1) / BRICK;
int o = offset[i];
for (int k = 0; k < c; k++)
for (int j = 0; j < b; j++)
for (int l = 0; l < a; l++) {
key[o] = bu[l] + nbu * (bv[j] + nbv * bw[k]);
value[o] = i;
o++;
}
}
__global__ void brick_ranges_kernel(const int *key, int npairs, int *start, int *end) {
const int i = blockIdx.x * blockDim.x + threadIdx.x;
if (i >= npairs)
return;
const int k = key[i];
if (i == 0 || key[i - 1] != k)
start[k] = i;
if (i == npairs - 1 || key[i + 1] != k)
end[k] = i + 1;
}
// An atom's box as the gather tests it: its first point, unwrapped (c - d) and wrapped into the grid, and its
// width less one (2 d), along each axis; and its centre in grid units.
struct GatherBox {
int lo[3], first[3], span[3];
float nctr[3];
};
// The point p's offset in the box along an axis of n points, 0 to span where it is in it.
__device__ __forceinline__ int box_offset(int p, int first, int n) {
const int m = p - first;
return m < 0 ? m + n : m;
}
// The density of the model on the grid, as UseDensityBoxesByPlane() and AtomDensity (ModelGrid.cpp) put
// it there, bit for bit: every point adds, in model order, each atom whose box holds it and whose radius
// reaches it, with the CPU's single-precision arithmetic in the CPU's order (no a*b+c is contracted:
// CMakeLists.txt compiles device code with --fmad=false). One block per brick; the brick's atoms are
// staged in shared memory. Supports() leaves only boxes narrower than the cell, so a point is in an atom's
// box at most once, at one index of the box's own unwrapped range.
__global__ void gather_kernel(const ModelDensityAtom *atoms, const float4 *pos, const int *box, const int *pair_atom,
const int *brick_start, const int *brick_end, ModelDensityGPU::Geometry g,
float *grid) {
const int nbu = (g.nu + BRICK - 1) / BRICK, nbv = (g.nv + BRICK - 1) / BRICK;
const int brick = blockIdx.x;
const int s = brick_start[brick], e = brick_end[brick]; // s == e: an empty brick, written as zeros
const int u = (brick % nbu) * BRICK + threadIdx.x, v = (brick / nbu % nbv) * BRICK + threadIdx.y,
w = (brick / (nbu * nbv)) * BRICK + threadIdx.z;
const bool inside = u < g.nu && v < g.nv && w < g.nw;
const int tid = threadIdx.x + BRICK * (threadIdx.y + BRICK * threadIdx.z);
const int n3[3] = {g.nu, g.nv, g.nw};
constexpr int WORDS = sizeof(ModelDensityAtom) / sizeof(int);
__shared__ int sh_index[GATHER_TILE];
__shared__ ModelDensityAtom sh_atom[GATHER_TILE];
__shared__ GatherBox sh_box[GATHER_TILE];
float acc = 0.0f;
for (int c = s; c < e; c += GATHER_TILE) {
const int m = min(GATHER_TILE, e - c);
__syncthreads();
if (tid < m) {
const int a = pair_atom[c + tid];
sh_index[tid] = a;
const float4 p = pos[a];
const float nctr[3] = {p.x, p.y, p.z};
GatherBox &b = sh_box[tid];
for (int k = 0; k < 3; k++) {
const int d = box[3 * a + k];
b.lo[k] = __float2int_rn(nctr[k]) - d;
b.first[k] = imod(b.lo[k], n3[k]);
b.span[k] = 2 * d;
b.nctr[k] = nctr[k];
}
}
__syncthreads();
for (int i = tid; i < m * WORDS; i += BRICK * BRICK * BRICK)
reinterpret_cast<int *>(sh_atom)[i] = reinterpret_cast<const int *>(atoms + sh_index[i / WORDS])[i % WORDS];
__syncthreads();
if (!inside)
continue;
for (int k = 0; k < m; k++) {
const GatherBox &b = sh_box[k];
const int mu = box_offset(u, b.first[0], g.nu), mv = box_offset(v, b.first[1], g.nv),
mw = box_offset(w, b.first[2], g.nw);
if (mu > b.span[0] || mv > b.span[1] || mw > b.span[2])
continue;
const ModelDensityAtom &at = sh_atom[k];
// f = centre - (u, v, w) in the box's own (unwrapped) indices, then in A, as the CPU walks it
const float fx = b.nctr[0] - static_cast<float>(b.lo[0] + mu);
const float fy = b.nctr[1] - static_cast<float>(b.lo[1] + mv);
const float fz = b.nctr[2] - static_cast<float>(b.lo[2] + mw);
const float z = g.m22 * fz;
const float y = g.m11 * fy + g.m12 * fz;
const float yz = y * y + z * z;
const float x = g.m00 * fx + (g.m01 * fy + g.m02 * fz);
const float r2 = yz + x * x;
if (r2 > at.max_r2)
continue;
float density = 0.0f;
if (!at.aniso) {
for (int q = 0; q < 5; q++)
density += at.a[q] * expapprox(fmaxf(at.b[q][0] * r2, -88.f));
} else {
for (int q = 0; q < 5; q++) {
const float *bq = at.b[q];
// gemmi's SMat33::r_u_r(), in its order
const float rur = x * x * bq[0] + y * y * bq[1] + z * z * bq[2] +
2 * (x * y * bq[3] + x * z * bq[4] + y * z * bq[5]);
density += at.a[q] * expapprox(fmaxf(rur, -88.f));
}
}
acc += at.occ * density;
}
}
if (inside)
grid[u + static_cast<size_t>(g.nu) * (v + static_cast<size_t>(g.nv) * w)] = acc;
}
int blocks(size_t n) {
return static_cast<int>((n + THREADS - 1) / THREADS);
}
// cub's temporary storage for the pair scan and sort at the capacity.
size_t CubBytes(size_t atoms, size_t pairs) {
size_t scan = 0, sort = 0;
cuda_err(cub::DeviceScan::ExclusiveSum(nullptr, scan, static_cast<int *>(nullptr), static_cast<int *>(nullptr),
static_cast<int>(atoms + 1)));
cuda_err(cub::DeviceRadixSort::SortPairs(nullptr, sort, static_cast<int *>(nullptr), static_cast<int *>(nullptr),
static_cast<int *>(nullptr), static_cast<int *>(nullptr),
static_cast<int>(pairs)));
return std::max(scan, sort);
}
} // namespace
// The most bricks the 2 d + 1 wrapped points of a box can fall in along an axis of n points: one more
// than the points span for where they start in a brick, and one more again where they wrap past a last
// brick that is partial (n = 17: the points 15, 16, 0 fall in bricks 1, 2 and 0).
size_t ModelDensityGPU::AxisBrickBound(int d, int n) {
const int nb = (n + BRICK - 1) / BRICK;
return std::min(nb, (2 * d + 1 + BRICK - 1) / BRICK + 2);
}
size_t ModelDensityGPU::Bricks(int nu, int nv, int nw) {
return static_cast<size_t>((nu + BRICK - 1) / BRICK) * ((nv + BRICK - 1) / BRICK) * ((nw + BRICK - 1) / BRICK);
}
std::vector<int> ModelDensityGPU::Boxes(const ModelDensityGrid &grid, const std::vector<ModelDensityAtom> &atoms) {
const int n3[3] = {grid.nu, grid.nv, grid.nw};
double spacing[3];
for (int k = 0; k < 3; k++)
spacing[k] = 1.0 / (n3[k] * std::sqrt(grid.frac[3 * k] * grid.frac[3 * k] + grid.frac[3 * k + 1] * grid.frac[3 * k + 1] +
grid.frac[3 * k + 2] * grid.frac[3 * k + 2]));
std::vector<int> box(3 * atoms.size());
for (size_t i = 0; i < atoms.size(); i++)
for (int k = 0; k < 3; k++)
box[3 * i + k] = static_cast<int>(std::ceil(atoms[i].radius / spacing[k]));
return box;
}
size_t ModelDensityGPU::PairBound(const ModelDensityGrid &grid, const std::vector<ModelDensityAtom> &atoms) {
const std::vector<int> box = Boxes(grid, atoms);
const int n3[3] = {grid.nu, grid.nv, grid.nw};
size_t pairs = 0;
for (size_t i = 0; i < atoms.size(); i++) {
size_t product = 1;
for (int k = 0; k < 3; k++)
product *= AxisBrickBound(box[3 * i + k], n3[k]);
pairs += product;
}
return pairs;
}
bool ModelDensityGPU::Supports(const ModelDensityGrid &grid, const std::vector<ModelDensityAtom> &atoms) {
const std::vector<int> box = Boxes(grid, atoms);
const int n3[3] = {grid.nu, grid.nv, grid.nw};
for (size_t i = 0; i < box.size(); i++)
if (2 * box[i] + 1 > n3[i % 3] || AxisBrickBound(box[i], n3[i % 3]) > MAX_BRICKS_PER_AXIS)
return false;
return true;
}
size_t ModelDensityGPU::DeviceBytes(size_t max_atoms, size_t max_pairs, size_t max_bricks) {
const size_t na = max_atoms + 1;
return na * (sizeof(ModelDensityAtom) + 3 * sizeof(int) + 2 * sizeof(int)) + 4 * max_pairs * sizeof(int) +
2 * max_bricks * sizeof(int) + CubBytes(na, max_pairs + 1);
}
ModelDensityGPU::ModelDensityGPU(cudaStream_t stream, size_t max_atoms_, size_t max_pairs_, size_t max_bricks_)
: stream(stream), max_atoms(max_atoms_), max_pairs(max_pairs_), max_bricks(max_bricks_) {
const auto sync = CudaAlloc::Synchronous;
const size_t na = std::max<size_t>(max_atoms, 1), np = std::max<size_t>(max_pairs, 1),
nb = std::max<size_t>(max_bricks, 1);
atoms = CudaDevicePtr<ModelDensityAtom>(na, sync);
box = CudaDevicePtr<int>(3 * na, sync);
overflow = CudaDevicePtr<int>(1, sync);
count = CudaDevicePtr<int>(na + 1, sync);
offset = CudaDevicePtr<int>(na + 1, sync);
key = CudaDevicePtr<int>(np, sync);
value = CudaDevicePtr<int>(np, sync);
key_sorted = CudaDevicePtr<int>(np, sync);
value_sorted = CudaDevicePtr<int>(np, sync);
brick_start = CudaDevicePtr<int>(nb, sync);
brick_end = CudaDevicePtr<int>(nb, sync);
cub_bytes = CubBytes(na, np);
cub_temp = CudaDevicePtr<char>(std::max<size_t>(cub_bytes, 1), sync);
}
void ModelDensityGPU::SetAtoms(const ModelDensityGrid &grid, const std::vector<ModelDensityAtom> &atom_list) {
if (atom_list.size() > max_atoms || Bricks(grid.nu, grid.nv, grid.nw) > max_bricks)
throw JFJochException(JFJochExceptionCategory::GPUCUDAError, "model density: grid or atoms over the reserve");
// An atom whose box is wider than the cell would reach a point through more than one image, which
// gemmi's box walk adds and the gather's box test does not; such a cell is left to the CPU.
if (!Supports(grid, atom_list))
throw JFJochException(JFJochExceptionCategory::GPUCUDAError, "model density: an atom wider than the cell");
geom.nu = grid.nu;
geom.nv = grid.nv;
geom.nw = grid.nw;
// As gemmi's Grid sets orth_n (multiply_by_diagonal with 1/n) and ModelDensityGeometry() rounds it.
const double inv_n[3] = {1.0 / grid.nu, 1.0 / grid.nv, 1.0 / grid.nw};
geom.m00 = static_cast<float>(grid.orth[0] * inv_n[0]);
geom.m01 = static_cast<float>(grid.orth[1] * inv_n[1]);
geom.m02 = static_cast<float>(grid.orth[2] * inv_n[2]);
geom.m11 = static_cast<float>(grid.orth[4] * inv_n[1]);
geom.m12 = static_cast<float>(grid.orth[5] * inv_n[2]);
geom.m22 = static_cast<float>(grid.orth[8] * inv_n[2]);
const std::vector<int> b = Boxes(grid, atom_list);
n_atoms = static_cast<int>(atom_list.size());
if (n_atoms > 0) {
cuda_err(cudaMemcpyAsync(atoms, atom_list.data(), atom_list.size() * sizeof(ModelDensityAtom),
cudaMemcpyHostToDevice, stream));
cuda_err(cudaMemcpyAsync(box, b.data(), b.size() * sizeof(int), cudaMemcpyHostToDevice, stream));
}
// The uploads read host vectors that end with this call.
cuda_err(cudaStreamSynchronize(stream));
}
void ModelDensityGPU::Compute(const float4 *d_pos, float *d_grid) {
cuda_err(cudaMemsetAsync(overflow, 0, sizeof(int), stream));
count_pairs_kernel<<<blocks(n_atoms + 1), THREADS, 0, stream>>>(d_pos, box, n_atoms, geom.nu, geom.nv, geom.nw,
count, overflow);
cuda_err(cudaGetLastError());
size_t temp = cub_bytes;
cuda_err(cub::DeviceScan::ExclusiveSum(cub_temp.get(), temp, count.get(), offset.get(), n_atoms + 1, stream));
int npairs = 0;
int over = 0;
cuda_err(cudaMemcpyAsync(&npairs, offset.get() + n_atoms, sizeof(int), cudaMemcpyDeviceToHost, stream));
cuda_err(cudaMemcpyAsync(&over, overflow.get(), sizeof(int), cudaMemcpyDeviceToHost, stream));
cuda_err(cudaStreamSynchronize(stream));
if (over)
throw JFJochException(JFJochExceptionCategory::GPUCUDAError, "model density: an atom's box over the bricks per axis");
if (static_cast<size_t>(npairs) > max_pairs)
throw JFJochException(JFJochExceptionCategory::GPUCUDAError, "model density: gather pairs over the reserve");
fill_pairs_kernel<<<blocks(n_atoms), THREADS, 0, stream>>>(d_pos, box, n_atoms, geom.nu, geom.nv, geom.nw,
offset, key, value);
cuda_err(cudaGetLastError());
const int nb = static_cast<int>(Bricks(geom.nu, geom.nv, geom.nw));
int bits = 1;
while ((1 << bits) < nb)
bits++;
temp = cub_bytes;
cuda_err(cub::DeviceRadixSort::SortPairs(cub_temp.get(), temp, key.get(), key_sorted.get(), value.get(),
value_sorted.get(), npairs, 0, bits, stream));
cuda_err(cudaMemsetAsync(brick_start, 0, nb * sizeof(int), stream));
cuda_err(cudaMemsetAsync(brick_end, 0, nb * sizeof(int), stream));
if (npairs > 0) {
brick_ranges_kernel<<<blocks(npairs), THREADS, 0, stream>>>(key_sorted, npairs, brick_start, brick_end);
cuda_err(cudaGetLastError());
}
gather_kernel<<<nb, dim3(BRICK, BRICK, BRICK), 0, stream>>>(atoms, d_pos, box, value_sorted, brick_start, brick_end,
geom, d_grid);
cuda_err(cudaGetLastError());
}