- #include "cuda_runtime.h"
- #include "device_launch_parameters.h"
- #include <stdio.h>
- //#include <cmath>
- #include<stdint.h>
- //typedef BYTE uint16_t;
- //typedef int uint16_t;
- #include "CudaKernelInfo.h"
- #include <iostream>
- //#include <iostream>
- using namespace std;
- cudaError_t addWithCuda(int *c, const int *a, const int *b, unsigned int size);
- __global__ void addKernel(int *c, const int *a, const int *b)
- {
- int i = threadIdx.x;
- c[i] = a[i] + b[i];
- }
- /*__device__ inline float lerp(float v0, float v1, float t)
- {
-
- return fmaf(t, v1, fmaf(-t, v0, v0));
- }*/
- __device__ float lerp(float v0, float v1, float t)
- {
- return fmaf(t, v1, fmaf(-t, v0, v0));
- }
- __global__ void VolumeProcessing_resizeAndMaskKernel(
- uint16_t * out_ptr, const int out_stride,
- const float * in_ptr, const int in_stride,
- const int out_size_x, const int out_size_y,
- const int in_size_x, const int in_size_y, const int in_size_z,
- int slice_index, float resample_step, float radius_sqr,
- const int max_voxel_value)
- {
- int ox = blockIdx.x*blockDim.x + threadIdx.x;
- int oy = blockIdx.y*blockDim.y + threadIdx.y;
- //std::cout << ox << " " << oy;
- if (ox >= out_size_x || oy >= out_size_y)
- {
- //cout << "exceed limit";
- return;
- }
-
-
- float dx = fmaf(0.5f, out_size_x, float(-ox) - 0.5f);
- float dy = fmaf(0.5f, out_size_y, float(-oy) - 0.5f);
- float d = fmaf(dx, dx, dy*dy);
-
- float value = 0.0f;
- if (d <= radius_sqr)
- {
- // clamp to edge
- float ix = resample_step * ox;
- float iy = resample_step * oy;
- float iz = resample_step * slice_index;
- // 0: first, 1: next voxel
- int x0 = min(int(ix) + 0, in_size_x - 1);
- int x1 = min(int(ix) + 1, in_size_x - 1);
- int y0 = min(int(iy) + 0, in_size_y - 1);
- int y1 = min(int(iy) + 1, in_size_y - 1);
- int z0 = min(int(iz) + 0, in_size_z - 1);
- int z1 = min(int(iz) + 1, in_size_z - 1);
- // weight of next voxel
- float t = min(ix - x0, 1.0f);
- float u = min(iy - y0, 1.0f);
- float v = min(iz - z0, 1.0f);
- float xy0 = lerp(
- lerp(in_ptr[x0 + (y0 + z0 * in_size_y) * in_stride]
- , in_ptr[x1 + (y0 + z0 * in_size_y) * in_stride], t),
- lerp(in_ptr[x0 + (y1 + z0 * in_size_y) * in_stride]
- , in_ptr[x1 + (y1 + z0 * in_size_y) * in_stride], t), u);
- float xy1 = lerp(
- lerp(in_ptr[x0 + (y0 + z1 * in_size_y) * in_stride]
- , in_ptr[x1 + (y0 + z1 * in_size_y) * in_stride], t),
- lerp(in_ptr[x0 + (y1 + z1 * in_size_y) * in_stride]
- , in_ptr[x1 + (y1 + z1 * in_size_y) * in_stride], t), u);
- value = lerp(xy0, xy1, v);
- }
- out_ptr[ox + oy * out_stride] = uint16_t(min(max(0.5f, value + 0.5f), 0.5f + max_voxel_value));
- }
- int main()
- {
- /* const int arraySize = 5;
- const int a[arraySize] = { 1, 2, 3, 4, 5 };
- const int b[arraySize] = { 10, 20, 30, 40, 50 };
- int c[arraySize] = { 0 };
- // Add vectors in parallel.
- cudaError_t cudaStatus = addWithCuda(c, a, b, arraySize);
- if (cudaStatus != cudaSuccess) {
- fprintf(stderr, "addWithCuda failed!");
- return 1;
- }
- printf("{1,2,3,4,5} + {10,20,30,40,50} = {%d,%d,%d,%d,%d}\n",
- c[0], c[1], c[2], c[3], c[4]); */
- // cudaDeviceReset must be called before exiting in order for profiling and
- // tracing tools such as Nsight and Visual Profiler to show complete traces.
- // test resample
- // add by yyy
-
- cudaError_t cudaStatus;
- cudaStatus = cudaSetDevice(0);
- if (cudaStatus != cudaSuccess) {
- fprintf(stderr, "cudaSetDevice failed! Do you have a CUDA-capable GPU installed?");
-
- }
- uint16_t *out_ptr;
- const int out_stride = 448;
- //const float *in_ptr;
- float *in_ptr;
- //void *v_in_ptr;
- const int in_stride = 480;
- const int out_size_x = 420;
- const int out_size_y = 420;
- const int in_size_x = 420;
- const int in_size_y = 420;
- const int in_size_z = 250;
- int slice_index = 0;
- float resample_step = 1;
- float radius_sqr = 209.5;
- const int max_voxel_value = 8191;
- //CUDACHECK
- //cudaMemset
- out_ptr = new uint16_t[420 * 420];
- //float *t1 = new float[420 * 420 * 250];
- [color=Red] // 执行到这里报错 an illegal memory access was encountered[/color]
- [color=Red]cudaStatus=cudaMalloc((void**)&in_ptr, 420 * 420 * 250 * sizeof(float));[/color]
-
- if (cudaStatus != cudaSuccess) {
- fprintf(stderr, "addKernel launch failed: %s\n", cudaGetErrorString(cudaStatus));
- }
-
- //cudaMemcpy(v_in_ptr, t1, 420 * 420 * 250 * sizeof(float), cudaMemcpyHostToDevice);
- //cudaMemcpy()
- //CudaKernelInfo launch(420, 420);
- //CudaKernelInfo launch(slice.sizeX(), slice.sizeY());
-
- // block size
- CudaKernelInfo launch(420, 420);
-
- //cout << launch.gridSize() << " " << launch.threadBlockSize();
-
- VolumeProcessing_resizeAndMaskKernel<<<launch.gridSize(),launch.threadBlockSize()>>>(out_ptr, out_stride, in_ptr, in_stride,
- out_size_x, out_size_y, in_size_x, in_size_y, in_size_z, slice_index, resample_step, radius_sqr, max_voxel_value);
- cudaStatus = cudaDeviceSynchronize();
- if (cudaStatus != cudaSuccess) {
- fprintf(stderr, "cudaDeviceSynchronize returned error code %d after launching addKernel!\n", cudaStatus);
- }
- /*cudaStatus = cudaDeviceReset();
- if (cudaStatus != cudaSuccess) {
- fprintf(stderr, "cudaDeviceReset failed!");
- return 1;
- }*/
- //cudaFreeArray(in_ptr);
- delete[]out_ptr;
- cudaFree(in_ptr);
-
- return 0;
- }
- // Helper function for using CUDA to add vectors in parallel.
- cudaError_t addWithCuda(int *c, const int *a, const int *b, unsigned int size)
- {
- int *dev_a = 0;
- int *dev_b = 0;
- int *dev_c = 0;
- cudaError_t cudaStatus;
- // Choose which GPU to run on, change this on a multi-GPU system.
- cudaStatus = cudaSetDevice(0);
- if (cudaStatus != cudaSuccess) {
- fprintf(stderr, "cudaSetDevice failed! Do you have a CUDA-capable GPU installed?");
- goto Error;
- }
- // Allocate GPU buffers for three vectors (two input, one output) .
- cudaStatus = cudaMalloc((void**)&dev_c, size * sizeof(int));
- if (cudaStatus != cudaSuccess) {
- fprintf(stderr, "cudaMalloc failed!");
- goto Error;
- }
- cudaStatus = cudaMalloc((void**)&dev_a, size * sizeof(int));
- if (cudaStatus != cudaSuccess) {
- fprintf(stderr, "cudaMalloc failed!");
- goto Error;
- }
- cudaStatus = cudaMalloc((void**)&dev_b, size * sizeof(int));
- if (cudaStatus != cudaSuccess) {
- fprintf(stderr, "cudaMalloc failed!");
- goto Error;
- }
- // Copy input vectors from host memory to GPU buffers.
- cudaStatus = cudaMemcpy(dev_a, a, size * sizeof(int), cudaMemcpyHostToDevice);
- if (cudaStatus != cudaSuccess) {
- fprintf(stderr, "cudaMemcpy failed!");
- goto Error;
- }
- cudaStatus = cudaMemcpy(dev_b, b, size * sizeof(int), cudaMemcpyHostToDevice);
- if (cudaStatus != cudaSuccess) {
- fprintf(stderr, "cudaMemcpy failed!");
- goto Error;
- }
- // Launch a kernel on the GPU with one thread for each element.
- addKernel<<<1, size>>>(dev_c, dev_a, dev_b);
- // Check for any errors launching the kernel
- cudaStatus = cudaGetLastError();
- if (cudaStatus != cudaSuccess) {
- fprintf(stderr, "addKernel launch failed: %s\n", cudaGetErrorString(cudaStatus));
- goto Error;
- }
-
- // cudaDeviceSynchronize waits for the kernel to finish, and returns
- // any errors encountered during the launch.
- cudaStatus = cudaDeviceSynchronize();
- if (cudaStatus != cudaSuccess) {
- fprintf(stderr, "cudaDeviceSynchronize returned error code %d after launching addKernel!\n", cudaStatus);
- goto Error;
- }
- // Copy output vector from GPU buffer to host memory.
- cudaStatus = cudaMemcpy(c, dev_c, size * sizeof(int), cudaMemcpyDeviceToHost);
- if (cudaStatus != cudaSuccess) {
- fprintf(stderr, "cudaMemcpy failed!");
- goto Error;
- }
- Error:
- cudaFree(dev_c);
- cudaFree(dev_a);
- cudaFree(dev_b);
-
- return cudaStatus;
- }
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