OneLLM / lib /pointnet2 /src /ball_query_gpu.cu
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#include <math.h>
#include <stdio.h>
#include <stdlib.h>
#include "ball_query_gpu.h"
#include "cuda_utils.h"
__global__ void ball_query_kernel_fast(int b, int n, int m, float radius, int nsample,
const float *__restrict__ new_xyz, const float *__restrict__ xyz, int *__restrict__ idx) {
// new_xyz: (B, M, 3)
// xyz: (B, N, 3)
// output:
// idx: (B, M, nsample)
int bs_idx = blockIdx.y;
int pt_idx = blockIdx.x * blockDim.x + threadIdx.x;
if (bs_idx >= b || pt_idx >= m) return;
new_xyz += bs_idx * m * 3 + pt_idx * 3;
xyz += bs_idx * n * 3;
idx += bs_idx * m * nsample + pt_idx * nsample;
float radius2 = radius * radius;
float new_x = new_xyz[0];
float new_y = new_xyz[1];
float new_z = new_xyz[2];
int cnt = 0;
for (int k = 0; k < n; ++k) {
float x = xyz[k * 3 + 0];
float y = xyz[k * 3 + 1];
float z = xyz[k * 3 + 2];
float d2 = (new_x - x) * (new_x - x) + (new_y - y) * (new_y - y) + (new_z - z) * (new_z - z);
if (d2 < radius2){
if (cnt == 0){
for (int l = 0; l < nsample; ++l) {
idx[l] = k;
}
}
idx[cnt] = k;
++cnt;
if (cnt >= nsample) break;
}
}
}
void ball_query_kernel_launcher_fast(int b, int n, int m, float radius, int nsample, \
const float *new_xyz, const float *xyz, int *idx, cudaStream_t stream) {
// new_xyz: (B, M, 3)
// xyz: (B, N, 3)
// output:
// idx: (B, M, nsample)
cudaError_t err;
dim3 blocks(DIVUP(m, THREADS_PER_BLOCK), b); // blockIdx.x(col), blockIdx.y(row)
dim3 threads(THREADS_PER_BLOCK);
ball_query_kernel_fast<<<blocks, threads, 0, stream>>>(b, n, m, radius, nsample, new_xyz, xyz, idx);
// cudaDeviceSynchronize(); // for using printf in kernel function
err = cudaGetLastError();
if (cudaSuccess != err) {
fprintf(stderr, "CUDA kernel failed : %s\n", cudaGetErrorString(err));
exit(-1);
}
}