text: // RUN: %run_test hipify "%s" "%t" %hipify_args %clang_args
  /*
  Copyright (c) 2015-present Advanced Micro Devices, Inc. All rights reserved.
  
  Permission is hereby granted, free of charge, to any person obtaining a copy
  of this software and associated documentation files (the "Software"), to deal
  in the Software without restriction, including without limitation the rights
  to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
  copies of the Software, and to permit persons to whom the Software is
  furnished to do so, subject to the following conditions:
  
  The above copyright notice and this permission notice shall be included in
  all copies or substantial portions of the Software.
  
  THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
  IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
  FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL THE
  AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
  LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
  OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
  THE SOFTWARE.
  */
  
  #include <iostream>
  // CHECK: #include <hip/hip_runtime.h>
  #include <cuda.h>
  #include <assert.h>
  #define WIDTH 32
  
  #define NUM (WIDTH * WIDTH)
  
  #define THREADS_PER_BLOCK_X 4
  #define THREADS_PER_BLOCK_Y 4
  #define THREADS_PER_BLOCK_Z 1
  
  using namespace std;
  
  #define KNRM "\x1B[0m"
  #define KRED "\x1B[31m"
  
  #define failed(...)                                                                                \
      printf("%serror: ", KRED);                                                                     \
      printf(__VA_ARGS__);                                                                           \
      printf("\n");                                                                                  \
      printf("error: TEST FAILED\n%s", KNRM);                                                        \
      abort();
  
  // CHECK: hipError_t localError = error;
  // CHECK: if ((localError != hipSuccess) && (localError != hipErrorPeerAccessAlreadyEnabled) &&
  // CHECK: (localError != hipErrorPeerAccessNotEnabled )) {
  // CHECK: printf("%serror: '%s'(%d) from %s at %s:%d%s\n", KRED, hipGetErrorString(localError),
  #define CUDACHECK(error)                                                                           \
      {                                                                                              \
          cudaError_t localError = error;                                                            \
          if ((localError != cudaSuccess) && (localError != cudaErrorPeerAccessAlreadyEnabled) &&    \
                       (localError != cudaErrorPeerAccessNotEnabled )) {                             \
              printf("%serror: '%s'(%d) from %s at %s:%d%s\n", KRED, cudaGetErrorString(localError), \
                     localError, #error, __FILE__, __LINE__, KNRM);                                  \
              failed("API returned error code.");                                                    \
          }                                                                                          \
      }
  
  void checkPeer2PeerSupport() {
      int gpuCount;
      int canAccessPeer;
      // CHECK: CUDACHECK(hipGetDeviceCount(&gpuCount));
      CUDACHECK(cudaGetDeviceCount(&gpuCount));
      for (int currentGpu = 0; currentGpu < gpuCount; currentGpu++) {
          // CHECK: CUDACHECK(hipSetDevice(currentGpu));
          CUDACHECK(cudaSetDevice(currentGpu));
          for (int peerGpu = 0; peerGpu < currentGpu; peerGpu++) {
              if (currentGpu != peerGpu) {
                  // CHECK: CUDACHECK(hipDeviceCanAccessPeer(&canAccessPeer, currentGpu, peerGpu));
                  CUDACHECK(cudaDeviceCanAccessPeer(&canAccessPeer, currentGpu, peerGpu));
                  printf("currentGpu#%d canAccessPeer: peerGpu#%d=%d\n", currentGpu, peerGpu,
                         canAccessPeer);
              }
              // CHECK: CUDACHECK(hipSetDevice(peerGpu));
              CUDACHECK(cudaSetDevice(peerGpu));
              // CHECK: CUDACHECK(hipDeviceReset());
              CUDACHECK(cudaDeviceReset());
          }
          // CHECK: CUDACHECK(hipSetDevice(currentGpu));
          CUDACHECK(cudaSetDevice(currentGpu));
          // CHECK: CUDACHECK(hipDeviceReset());
          CUDACHECK(cudaDeviceReset());
      }
  }
  
  void enablePeer2Peer(int currentGpu, int peerGpu) {
      int canAccessPeer;
      // Must be on a multi-gpu system:
      assert(currentGpu != peerGpu);
      // CHECK: CUDACHECK(hipSetDevice(currentGpu));
      CUDACHECK(cudaSetDevice(currentGpu));
      // CHECK: hipDeviceCanAccessPeer(&canAccessPeer, currentGpu, peerGpu);
      cudaDeviceCanAccessPeer(&canAccessPeer, currentGpu, peerGpu);
      if (canAccessPeer == 1) {
          // CHECK: CUDACHECK(hipDeviceEnablePeerAccess(peerGpu, 0));
          CUDACHECK(cudaDeviceEnablePeerAccess(peerGpu, 0));
      } else
          printf("peer2peer transfer not possible between the selected gpu devices");
  }
  
  void disablePeer2Peer(int currentGpu, int peerGpu) {
      int canAccessPeer;
      // Must be on a multi-gpu system:
      assert(currentGpu != peerGpu);
      // CHECK: CUDACHECK(hipSetDevice(currentGpu));
      CUDACHECK(cudaSetDevice(currentGpu));
      // CHECK: hipDeviceCanAccessPeer(&canAccessPeer, currentGpu, peerGpu);
      cudaDeviceCanAccessPeer(&canAccessPeer, currentGpu, peerGpu);
      if (canAccessPeer == 1) {
          // CHECK: CUDACHECK(hipDeviceDisablePeerAccess(peerGpu));
          CUDACHECK(cudaDeviceDisablePeerAccess(peerGpu));
      } else
          printf("peer2peer disable not required");
  }
  
  __global__ void matrixTranspose_static_shared(float* out, float* in,
                                                const int width) {
      // CHECK-NOT: HIP_DYNAMIC_SHARED(float, sharedMem);
      // CHECK: __shared__ float sharedMem[WIDTH * WIDTH];
      __shared__ float sharedMem[WIDTH * WIDTH];
      int x = blockDim.x * blockIdx.x + threadIdx.x;
      int y = blockDim.y * blockIdx.y + threadIdx.y;
      sharedMem[y * width + x] = in[x * width + y];
      __syncthreads();
      out[y * width + x] = sharedMem[y * width + x];
  }
  
  __global__ void matrixTranspose_dynamic_shared(float* out, float* in,
                                                 const int width) {
      // declare dynamic shared memory
      // CHECK-NOT: extern __shared__
      // CHECK: HIP_DYNAMIC_SHARED(float, sharedMem)
      extern __shared__ float sharedMem[];
      int x = blockDim.x * blockIdx.x + threadIdx.x;
      int y = blockDim.y * blockIdx.y + threadIdx.y;
      sharedMem[y * width + x] = in[x * width + y];
      __syncthreads();
      out[y * width + x] = sharedMem[y * width + x];
  }
  
  int main() {
      checkPeer2PeerSupport();
      int gpuCount;
      int currentGpu, peerGpu;
      // CHECK: CUDACHECK(hipGetDeviceCount(&gpuCount));
      CUDACHECK(cudaGetDeviceCount(&gpuCount));
      if (gpuCount < 2) {
          printf("Peer2Peer application requires atleast 2 gpu devices");
          return 0;
      }
      currentGpu = 0;
      peerGpu = (currentGpu + 1);
      printf("currentGpu=%d peerGpu=%d (Total no. of gpu = %d)\n", currentGpu, peerGpu, gpuCount);
      float *data[2], *TransposeMatrix[2], *gpuTransposeMatrix[2], *randArray;
      int width = WIDTH;
      randArray = (float*)malloc(NUM * sizeof(float));
      for (int i = 0; i < NUM; i++) {
          randArray[i] = (float)i * 1.0f;
      }
      enablePeer2Peer(currentGpu, peerGpu);
      // CHECK: CUDACHECK(hipSetDevice(currentGpu));
      CUDACHECK(cudaSetDevice(currentGpu));
      TransposeMatrix[0] = (float*)malloc(NUM * sizeof(float));
      // CHECK: hipMalloc((void**)&gpuTransposeMatrix[0], NUM * sizeof(float));
      cudaMalloc((void**)&gpuTransposeMatrix[0], NUM * sizeof(float));
      // CHECK: hipMalloc((void**)&data[0], NUM * sizeof(float));
      cudaMalloc((void**)&data[0], NUM * sizeof(float));
      // CHECK: hipMemcpy(data[0], randArray, NUM * sizeof(float), hipMemcpyHostToDevice);
      cudaMemcpy(data[0], randArray, NUM * sizeof(float), cudaMemcpyHostToDevice);
      dim3 dimGrid(WIDTH / THREADS_PER_BLOCK_X, WIDTH / THREADS_PER_BLOCK_Y);
      dim3 dimBlock(THREADS_PER_BLOCK_X, THREADS_PER_BLOCK_Y);
      // CHECK: hipLaunchKernelGGL(matrixTranspose_static_shared, dim3(dimGrid), dim3(dimBlock), 0, 0, gpuTransposeMatrix[0], data[0], width);
      matrixTranspose_static_shared <<<dimGrid, dimBlock>>>(gpuTransposeMatrix[0], data[0], width);
      // CHECK: CUDACHECK(hipSetDevice(peerGpu));
      CUDACHECK(cudaSetDevice(peerGpu));
      TransposeMatrix[1] = (float*)malloc(NUM * sizeof(float));
      // CHECK: hipMalloc((void**)&gpuTransposeMatrix[1], NUM * sizeof(float));
      cudaMalloc((void**)&gpuTransposeMatrix[1], NUM * sizeof(float));
      // CHECK: hipMalloc((void**)&data[1], NUM * sizeof(float));
      cudaMalloc((void**)&data[1], NUM * sizeof(float));
      // CHECK: hipMemcpy(data[1], gpuTransposeMatrix[0], NUM * sizeof(float), hipMemcpyDeviceToDevice);
      cudaMemcpy(data[1], gpuTransposeMatrix[0], NUM * sizeof(float), cudaMemcpyDeviceToDevice);
      // CHECK: hipLaunchKernelGGL(matrixTranspose_dynamic_shared, dim3(dimGrid), dim3(dimBlock), sizeof(float) * WIDTH * WIDTH, 0, gpuTransposeMatrix[1], data[1], width);
      matrixTranspose_dynamic_shared <<<dimGrid, dimBlock, sizeof(float) * WIDTH * WIDTH>>>(gpuTransposeMatrix[1], data[1], width);
      // CHECK: hipMemcpy(TransposeMatrix[1], gpuTransposeMatrix[1], NUM * sizeof(float), hipMemcpyDeviceToHost);
      cudaMemcpy(TransposeMatrix[1], gpuTransposeMatrix[1], NUM * sizeof(float), cudaMemcpyDeviceToHost);
      // CHECK: hipDeviceSynchronize();
      cudaDeviceSynchronize();
      disablePeer2Peer(currentGpu, peerGpu);
      // verify the results
      int errors = 0;
      double eps = 1.0E-6;
      for (int i = 0; i < NUM; i++) {
          if (std::abs(randArray[i] - TransposeMatrix[1][i]) > eps) {
              printf("%d cpu: %f gpu peered data  %f\n", i, randArray[i], TransposeMatrix[1][i]);
              errors++;
          }
      }
      if (errors != 0) {
          printf("FAILED: %d errors\n", errors);
      } else {
          printf("Peer2Peer PASSED!\n");
      }
      free(randArray);
      for (int i = 0; i < 2; i++) {
          // CHECK: hipFree(data[i]);
          cudaFree(data[i]);
          // CHECK: hipFree(gpuTransposeMatrix[i]);
          cudaFree(gpuTransposeMatrix[i]);
          free(TransposeMatrix[i]);
      }
      // CHECK: CUDACHECK(hipSetDevice(peerGpu));
      CUDACHECK(cudaSetDevice(peerGpu));
      // CHECK: CUDACHECK(hipDeviceReset());
      CUDACHECK(cudaDeviceReset());
      // CHECK: CUDACHECK(hipSetDevice(currentGpu));
      CUDACHECK(cudaSetDevice(currentGpu));
      // CHECK: CUDACHECK(hipDeviceReset());
      CUDACHECK(cudaDeviceReset());
      return 0;
  }
  