Hi,
I have this code:

%%cu
#include <stdio.h>
#include <stdlib.h>
#include <cuda.h>
#include <cuda_runtime.h>
#include "/content/common.h"

#define MATRIX_SIZE 1024
#define THREADS_PER_BLOCK 32

// Bitonic sort implementation
__device__ void bitonicSort(int* data, int k, int j, int dir) {
  int i, temp;

  if ((k & j) == 0) {
    i = threadIdx.x / k;
    if ((i & j) == 0) {
      if (dir == 1) {
        if (data[i * k + j] > data[i * k + j + k / 2]) {
          temp = data[i * k + j];
          data[i * k + j] = data[i * k + j + k / 2];
          data[i * k + j + k / 2] = temp;
        }
      } else {
        if (data[i * k + j] < data[i * k + j + k / 2]) {
          temp = data[i * k + j];
          data[i * k + j] = data[i * k + j + k / 2];
          data[i * k + j + k / 2] = temp;
        }
      }
    }
  }
}

__global__ void sortKernel(int* data, int width, int height) {
  int row = blockIdx.x * blockDim.x + threadIdx.x;
  if (row < height) {
    // Sort the subsequence of integers using bitonic sort
    for (int k = 2; k <= width; k *= 2) {
      for (int j = k / 2; j > 0; j /= 2) {
        bitonicSort(data + row * width, k, j, 1);
      }
    }
  }
}

__global__ void mergeKernel(int* data, int width, int height, int iteration) {
  int row = blockIdx.x * blockDim.x + threadIdx.x;
  if (row < height) {
    // Calculate the indices for merging the previously sorted halves
    int blockSize = width / (1 << iteration);
    int blockIndex = row / blockSize;
    int indexInBlock = row % blockSize;

    // Calculate the starting indices for the two halves to be merged
    int leftStart = blockIndex * blockSize;
    int rightStart = leftStart + blockSize / 2;

    // Merge the two sorted halves into a single sorted subsequence
    for (int k = blockSize / 2; k >= 1; k /= 2) {
      int j = indexInBlock % k;
      int leftIndex = leftStart + indexInBlock - j;
      int rightIndex = rightStart + indexInBlock - j;

      if (leftIndex < width && rightIndex < width) {
        if (data[leftIndex] > data[rightIndex]) {
          int temp = data[leftIndex];
          data[leftIndex] = data[rightIndex];
          data[rightIndex] = temp;
        }
      } else {
        printf("Invalid memory access in mergeKernel.\n");
      }
      __syncthreads();
    }
  } else {
    printf("Invalid memory access in mergeKernel.\n");
  }
}

bool isSorted(int* data, int size) {
  for (int i = 0; i < size - 1; i++) {
    if (data[i] > data[i + 1])
      return false;
  }
  return true;
}

int main() {
  const int dataSize = MATRIX_SIZE * MATRIX_SIZE;
  /* set up the device */
  int dev = 0;
  cudaDeviceProp deviceProp;
  CHECK(cudaGetDeviceProperties(&deviceProp, dev));
  printf("Using Device %d: %s\n", dev, deviceProp.name);
  CHECK(cudaSetDevice(dev));


  // Read the input data from file
  FILE* inputFile = fopen("/content/datSeq1M.bin", "rb");
  int* hostData = (int*)malloc(dataSize * sizeof(int));
  fseek(inputFile, sizeof(int), SEEK_SET); // Skip the first integer
  fread(hostData, sizeof(int), dataSize, inputFile);
  fclose(inputFile);

  // Print the sorted data
  for (int i = 0; i < dataSize; i++) {
    printf("%d ", hostData[i]);
    if( i == 10 ) break;
  }
  printf("\n");
  // Allocate memory on GPU
  int* deviceData;
  CHECK(cudaMalloc((void**)&deviceData, dataSize * sizeof(int)));

  // Copy data to GPU
  CHECK(cudaMemcpy(deviceData, hostData, dataSize * sizeof(int), cudaMemcpyHostToDevice));

  /* run the computational kernel */
  unsigned int gridDimX, gridDimY, gridDimZ, blockDimX, blockDimY, blockDimZ;
  blockDimX = THREADS_PER_BLOCK;
  blockDimY = 1;
  blockDimZ = 1;
  gridDimX = (dataSize + blockDimX - 1) / blockDimX;
  gridDimY = 1;
  gridDimZ = 1;

  dim3 grid(gridDimX, gridDimY, gridDimZ);
  dim3 block(blockDimX, blockDimY, blockDimZ);
  
  // Launch the sorting kernels in iterations
  int width = MATRIX_SIZE;
  int height = MATRIX_SIZE;
  for (int iteration = 1; iteration <= 10; iteration++) {
    sortKernel<<<grid, block>>>(deviceData, width, height);
    CHECK (cudaDeviceSynchronize ());                            // wait for kernel to finish
    CHECK (cudaGetLastError ());                                 // check for kernel errors

    // Merge the previously sorted halves
    mergeKernel<<<grid, block>>>(deviceData, width, height, iteration);
    CHECK (cudaDeviceSynchronize ());                            // wait for kernel to finish
    CHECK (cudaGetLastError ());                                 // check for kernel errors

    // Update the width and height for the next iteration
    width *= 2;
    height /= 2;
  }

  // Copy sorted data back to CPU
  cudaMemcpy(hostData, deviceData, dataSize * sizeof(int), cudaMemcpyDeviceToHost);

  // Check if the array is sorted
  bool isOrdered = isSorted(hostData, dataSize);

  // Print the sorted data
  for (int i = 0; i < dataSize; i++) {
    printf("%d ", hostData[i]);
    if( i == 10 ) break;
  }
  printf("\n");

  // Print the result of the ordering check
  if (isOrdered) {
    printf("The array is ordered.\n");
  } else {
    printf("The array is not ordered.\n");
  }

  // Free GPU memory
  cudaFree(deviceData);

  // Free CPU memory
  free(hostData);

  return 0;
}


And it is supposed to do this:
The kernels to be written should sort the contents of the file datSeq1M.bin in 10 iteration
steps. In iteration 1, 1024 subsequences of 1024 integer values are to be sorted in parallel. In
iteration 2, 512 subsequences of 2048 integer values are to be sorted in parallel based on the
merging of the previously sorted halves. And so on and so forth, until iteration 10 is reached,
where 2 previously sorted subsequences of 512K values are merged, yielding the whole sorted
sequence.
Assume that the values of the whole sequence, when stored in memory, are organized as the
elements of 1024 X 1024 matrix. The threads in a block thread process successive matrix rows.

But im getting this error:
Error: /tmp/tmp2rhhmu8n/208c30b5-68a7-4c2b-881c-f2b5913f6acd.cu:135, code: 700, reason: an illegal memory access was encountered

Fix it and give me the full code please