bool run_add() {
  
  constexpr size_t N = 64;
  std::vector<T> host_input(N);
  std::vector<T> host_expected(N);
  for (int i = 0; i < N; ++i) {
    host_input[i] = (T)i;
    host_expected[i] = host_input[i] + host_input[i];
  }

  T* input1;
  hipMalloc(&input1, N * sizeof(T));
  hipMemcpy(input1, host_input.data(), host_input.size()*sizeof(T), hipMemcpyHostToDevice);


  T* input2;
  hipMalloc(&input2, N * sizeof(T));
  hipMemcpy(input2, host_input.data(), host_input.size()*sizeof(T), hipMemcpyHostToDevice);


  constexpr unsigned int blocks = 1;
  constexpr unsigned int threads_per_block = 1;
  hipLaunchKernelGGL(add<T>, dim3(blocks), dim3(threads_per_block), 0, 0, input1, input2, N);

  hipMemcpy(host_input.data(), input1, host_input.size()*sizeof(T), hipMemcpyDeviceToHost);

  bool equal = true;
  for (int i = 0; i < N; i++) {
    equal &= (host_input[i] == host_expected[i]);
  }
  return equal;
}

int test_gl2(size_t N) {

    size_t Nbytes = N*sizeof(int);

    int *A_d, *B_d, *C_d;
    int *A_h, *B_h, *C_h;

    HipTest::initArrays (&A_d, &B_d, &C_d, &A_h, &B_h, &C_h, N);



    unsigned blocks = HipTest::setNumBlocks(blocksPerCU, threadsPerBlock, N);


    // Full vadd in one large chunk, to get things started:
    HIPCHECK ( hipMemcpy(A_d, A_h, Nbytes, hipMemcpyHostToDevice));
    HIPCHECK ( hipMemcpy(B_d, B_h, Nbytes, hipMemcpyHostToDevice));

    hipLaunchKernel(vectorADD2, dim3(blocks), dim3(threadsPerBlock), 0, 0, A_d, B_d, C_d, N);

    HIPCHECK ( hipMemcpy(C_h, C_d, Nbytes, hipMemcpyDeviceToHost));

    HIPCHECK (hipDeviceSynchronize());

    HipTest::checkVectorADD(A_h, B_h, C_h, N);

    return 0;

}

bool run_rint() {
    double *A, *Ad;
    double *B, *Bd;
    A = new double[N];
    B = new double[N];
    for (int i = 0; i < N; i++) {
        A[i] = 1.345;
    }
    hipMalloc((void**)&Ad, SIZE);
    hipMalloc((void**)&Bd, SIZE);
    hipMemcpy(Ad, A, SIZE, hipMemcpyHostToDevice);
    hipLaunchKernelGGL(test_rint, dim3(1), dim3(N), 0, 0, Ad, Bd);
    hipMemcpy(B, Bd, SIZE, hipMemcpyDeviceToHost);
    int passed = 0;
    for (int i = 0; i < 512; i++) {
        double x = round(A[i]);
        if (B[i] == x) {
            passed = 1;
        }
    }

    delete[] A;
    delete[] B;
    hipFree(Ad);
    hipFree(Bd);

    if (passed == 1) {
        return true;
    }
    assert(passed == 1);
    return false;
}

int main(){
    int A=0, *Ad;
    hipMalloc((void**)&Ad, SIZE);
    hipMemcpy(Ad, &A, SIZE, hipMemcpyHostToDevice);
    hipLaunchKernel(HIP_KERNEL_NAME(Iter), dim3(1), dim3(1), 0, 0, Ad);
    hipMemcpy(&A, Ad, SIZE, hipMemcpyDeviceToHost);
}

int main(int argc, char *argv[])
{ int warpSize, pshift;
  hipDeviceProp_t devProp;
  hipDeviceGetProperties(&devProp, 0);
  if(strncmp(devProp.name,"Fiji",1)==0)  {warpSize =64; pshift =6;}
  else {warpSize =32; pshift =5;}
  unsigned int Num_Threads_per_Block      = 512;
  unsigned int Num_Blocks_per_Grid        = 1;
  unsigned int Num_Warps_per_Block        = Num_Threads_per_Block/warpSize;
  unsigned int Num_Warps_per_Grid         = (Num_Threads_per_Block*Num_Blocks_per_Grid)/warpSize;
  unsigned int* host_ballot = (unsigned int*)malloc(Num_Warps_per_Grid*sizeof(unsigned int));
  unsigned int* device_ballot; 
  HIP_ASSERT(hipMalloc((void**)&device_ballot, Num_Warps_per_Grid*sizeof(unsigned int)));
  int divergent_count =0;
  for (int i=0; i<Num_Warps_per_Grid; i++) host_ballot[i] = 0;

 
  HIP_ASSERT(hipMemcpy(device_ballot, host_ballot, Num_Warps_per_Grid*sizeof(unsigned int), hipMemcpyHostToDevice));

  hipLaunchKernel(gpu_ballot, dim3(Num_Blocks_per_Grid),dim3(Num_Threads_per_Block),0,0, device_ballot,Num_Warps_per_Block,pshift);


  HIP_ASSERT(hipMemcpy(host_ballot, device_ballot, Num_Warps_per_Grid*sizeof(unsigned int), hipMemcpyDeviceToHost));
  for (int i=0; i<Num_Warps_per_Grid; i++) {

     if ((host_ballot[i] == 0)||(host_ballot[i]/warpSize == warpSize)) std::cout << "Warp " << i << " IS convergent- Predicate true for " << host_ballot[i]/warpSize << " threads\n";

     else {std::cout << "Warp " << i << " IS divergent - Predicate true for " << host_ballot[i]/warpSize<< " threads\n";
	  divergent_count++;}
}

if (divergent_count==1) printf("PASSED\n"); else printf("FAILED\n");
  return EXIT_SUCCESS;

}

bool run_lround(){
double *A, *Ad;
long int *B, *Bd;
A = new double[N];
B = new long int[N];
for(int i=0;i<N;i++){
A[i] = 1.345;
}
hipMalloc((void**)&Ad, SIZE);
hipMalloc((void**)&Bd, N*sizeof(long int));
hipMemcpy(Ad, A, SIZE, hipMemcpyHostToDevice);
hipLaunchKernel(test_lround, dim3(1), dim3(N), 0, 0, Ad, Bd);
hipMemcpy(B, Bd, N*sizeof(long int), hipMemcpyDeviceToHost);
int passed = 0;
for(int i=0;i<512;i++){
    long int x = round(A[i]);
    if(B[i] == x){
        passed = 1;
    }
}
free(A);
if(passed == 1){
    return true;
}
assert(passed == 1);
return false;
}

bool run_rnorm(){
double *A, *Ad, *B, *Bd;
A = new double[N];
B = new double[N];
double val = 0.0;
for(int i=0;i<N;i++){
A[i] = 1.0;
B[i] = 0.0;
val += 1.0;
}
val = 1/sqrt(val);
hipMalloc((void**)&Ad, SIZE);
hipMalloc((void**)&Bd, SIZE);
hipMemcpy(Ad, A, SIZE, hipMemcpyHostToDevice);
hipLaunchKernel(test_rnorm, dim3(1), dim3(N), 0, 0, Ad, Bd);
hipMemcpy(B, Bd, SIZE, hipMemcpyDeviceToHost);
int passed = 0;
for(int i=0;i<512;i++){
    if(B[0] - val < 0.000001){
        passed = 1;
    }
}
free(A);
if(passed == 1){
    return true;
}
assert(passed == 1);
return false;
}

bool run_rnorm3d(){
double *A, *Ad, *B, *Bd, *C, *Cd, *D, *Dd;
A = new double[N];
B = new double[N];
C = new double[N];
D = new double[N];
double val = 0.0;
for(int i=0;i<N;i++){
A[i] = 1.0;
B[i] = 2.0;
C[i] = 3.0;
}
val = 1/sqrt(1.0 + 4.0 + 9.0);
hipMalloc((void**)&Ad, SIZE);
hipMalloc((void**)&Bd, SIZE);
hipMalloc((void**)&Cd, SIZE);
hipMalloc((void**)&Dd, SIZE);
hipMemcpy(Ad, A, SIZE, hipMemcpyHostToDevice);
hipMemcpy(Bd, B, SIZE, hipMemcpyHostToDevice);
hipMemcpy(Cd, C, SIZE, hipMemcpyHostToDevice);
hipLaunchKernel(test_rnorm3d, dim3(1), dim3(N), 0, 0, Ad, Bd, Cd, Dd);
hipMemcpy(D, Dd, SIZE, hipMemcpyDeviceToHost);
int passed = 0;
for(int i=0;i<512;i++){
    if(D[i] - val < 0.000001){
        passed = 1;
    }
}
free(A);
if(passed == 1){
    return true;
}
assert(passed == 1);
return false;
}

bool run_erfinv(){
double *A, *Ad, *B, *Bd;
A = new double[N];
B = new double[N];
for(int i=0;i<N;i++){
A[i] = -0.6;
B[i] = 0.0;
}
hipMalloc((void**)&Ad, SIZE);
hipMalloc((void**)&Bd, SIZE);
hipMemcpy(Ad, A, SIZE, hipMemcpyHostToDevice);
hipLaunchKernel(test_erfinv, dim3(1), dim3(N), 0, 0, Ad, Bd);
hipMemcpy(B, Bd, SIZE, hipMemcpyDeviceToHost);
int passed = 0;
for(int i=0;i<512;i++){
    if(B[i] - A[i] < 0.000001){
        passed = 1;
    }
}
free(A);
if(passed == 1){
    return true;
}
assert(passed == 1);
return false;
}

bool run_sincos(){
double *A, *Ad, *B, *C, *Bd, *Cd;
A = new double[N];
B = new double[N];
C = new double[N];
for(int i=0;i<N;i++){
A[i] = 1.0;
}
hipMalloc((void**)&Ad, SIZE);
hipMalloc((void**)&Bd, SIZE);
hipMalloc((void**)&Cd, SIZE);
hipMemcpy(Ad, A, SIZE, hipMemcpyHostToDevice);
hipLaunchKernel(test_sincos, dim3(1), dim3(N), 0, 0, Ad, Bd, Cd);
hipMemcpy(B, Bd, SIZE, hipMemcpyDeviceToHost);
hipMemcpy(C, Cd, SIZE, hipMemcpyDeviceToHost);
int passed = 0;
for(int i=0;i<512;i++){
    if(B[i] == sin(1.0)){
        passed = 1;
    }
}
passed = 0;
for(int i=0;i<512;i++){
    if(C[i] == cos(1.0)){
        passed = 1;
    }
}
free(A);
if(passed == 1){
    return true;
}
assert(passed == 1);
return false;
}

void run(size_t size, hipStream_t stream1, hipStream_t stream2){
	float *Ah, *Bh, *Cd, *Dd, *Eh;
	float *Ahh, *Bhh, *Cdd, *Ddd, *Ehh;

	HIPCHECK(hipHostMalloc((void**)&Ah, size, hipHostMallocDefault));
	HIPCHECK(hipHostMalloc((void**)&Bh, size, hipHostMallocDefault));
	HIPCHECK(hipMalloc(&Cd, size));
	HIPCHECK(hipMalloc(&Dd, size));
	HIPCHECK(hipHostMalloc((void**)&Eh, size, hipHostMallocDefault));
	HIPCHECK(hipHostMalloc((void**)&Ahh, size, hipHostMallocDefault));
	HIPCHECK(hipHostMalloc((void**)&Bhh, size, hipHostMallocDefault));
	HIPCHECK(hipMalloc(&Cdd, size));
	HIPCHECK(hipMalloc(&Ddd, size));
	HIPCHECK(hipHostMalloc((void**)&Ehh, size, hipHostMallocDefault));

	HIPCHECK(hipMemcpyAsync(Bh, Ah, size, hipMemcpyHostToHost, stream1));
	HIPCHECK(hipMemcpyAsync(Bhh, Ahh, size, hipMemcpyHostToHost, stream2));
	HIPCHECK(hipMemcpyAsync(Cd, Bh, size, hipMemcpyHostToDevice, stream1));
	HIPCHECK(hipMemcpyAsync(Cdd, Bhh, size, hipMemcpyHostToDevice, stream2));
	hipLaunchKernel(HIP_KERNEL_NAME(Inc), dim3(N/500), dim3(500), 0, stream1, Cd);
	hipLaunchKernel(HIP_KERNEL_NAME(Inc), dim3(N/500), dim3(500), 0, stream2, Cdd);
	HIPCHECK(hipMemcpyAsync(Dd, Cd, size, hipMemcpyDeviceToDevice, stream1));
	HIPCHECK(hipMemcpyAsync(Ddd, Cdd, size, hipMemcpyDeviceToDevice, stream2));
	HIPCHECK(hipMemcpyAsync(Eh, Dd, size, hipMemcpyDeviceToHost, stream1));
	HIPCHECK(hipMemcpyAsync(Ehh, Ddd, size, hipMemcpyDeviceToHost, stream2));
	HIPCHECK(hipDeviceSynchronize());
	HIPASSERT(Eh[10] = Ah[10] + 1.0f);
	HIPASSERT(Ehh[10] = Ahh[10] + 1.0f);
}

int main(int argc, char *argv[])
{ int warpSize, pshift;
  hipDeviceProp_t devProp;
  hipGetDeviceProperties(&devProp, 0);
  if(strncmp(devProp.name,"Fiji",1)==0)
{ warpSize =64;
  pshift =6;
}
  else {warpSize =32; pshift=5;}
  int anycount =0;
  int allcount =0;
  int Num_Threads_per_Block      = 1024;
  int Num_Blocks_per_Grid        = 1;
  int Num_Warps_per_Block        = Num_Threads_per_Block/warpSize;
  int Num_Warps_per_Grid         = (Num_Threads_per_Block*Num_Blocks_per_Grid)/warpSize;

  int * host_any  = ( int*)malloc(Num_Warps_per_Grid*sizeof(int));
  int * host_all  = ( int*)malloc(Num_Warps_per_Grid*sizeof(int));
  int *device_any;
  int *device_all;
  HIP_ASSERT(hipMalloc((void**)&device_any,Num_Warps_per_Grid*sizeof( int)));
  HIP_ASSERT(hipMalloc((void**)&device_all,Num_Warps_per_Grid*sizeof(int)));
for (int i=0; i<Num_Warps_per_Grid; i++)
{
	host_any[i] = 0;
	host_all[i] = 0;
}
  HIP_ASSERT(hipMemcpy(device_any, host_any,sizeof(int), hipMemcpyHostToDevice));
  HIP_ASSERT(hipMemcpy(device_all, host_all,sizeof(int), hipMemcpyHostToDevice));

  hipLaunchKernel(warpvote, dim3(Num_Blocks_per_Grid),dim3(Num_Threads_per_Block),0,0, device_any, device_all ,Num_Warps_per_Block,pshift);


  HIP_ASSERT(hipMemcpy(host_any, device_any, Num_Warps_per_Grid*sizeof(int), hipMemcpyDeviceToHost));
  HIP_ASSERT(hipMemcpy(host_all, device_all, Num_Warps_per_Grid*sizeof(int), hipMemcpyDeviceToHost));
  for (int i=0; i<Num_Warps_per_Grid; i++) {

    printf("warp no. %d __any = %d \n",i,host_any[i]);
    printf("warp no. %d __all = %d \n",i,host_all[i]);

    if (host_all[i]!=1) ++allcount;
#if defined (__HIP_PLATFORM_HCC__) &&  !defined ( NVCC_COMPAT )
    if (host_any[i]!=64) ++anycount;
#else
    if (host_any[i]!=1) ++anycount;
#endif
}

#if defined (__HIP_PLATFORM_HCC__) &&  !defined ( NVCC_COMPAT )
    if (anycount == 1 && allcount ==1) printf("PASSED\n"); else printf("FAILED\n");
#else
    if (anycount == 0 && allcount ==1) printf("PASSED\n"); else printf("FAILED\n");
#endif

  return EXIT_SUCCESS;

}

int main() {
    hipLaunchKernelGGL(
        compileDoublePrecisionMathOnDevice,
        dim3(1, 1, 1),
        dim3(1, 1, 1),
        0,
        0,
        1);
    passed();
}

    void operator()(dim3 *grid_dim, dim3 *block_dim, int x, int y, int z)
    {
        if (y >= 4) {
            *block_dim = dim3(128, 4, 1);
        } else {
            *block_dim = dim3(512, 1, 1);
        }

        grid_dim->x = divide_and_round_up(x, block_dim->x);
        grid_dim->y = divide_and_round_up(y, block_dim->y);
        grid_dim->z = divide_and_round_up(z, block_dim->z);
    }

void BlockArrangement::ArrangePrefer3dLocality(dim3* grid, dim3* block,
                                               const uint3& volume_size)
{
    if (!grid || !block)
        return;

    int bw = 8;
    int bh = 8;
    int bd = 8;
    *block = dim3(bw, bh, bd);
    *grid = dim3((volume_size.x + bw - 1) / bw, (volume_size.y + bh - 1) / bh,
                 (volume_size.z + bd - 1) / bd);
}

void runTest(int argc, char **argv)
{
    hipDeviceProp_t deviceProp;
    deviceProp.major = 0;
    deviceProp.minor = 0;
    int dev = 0;

    hipDeviceGetProperties(&deviceProp, dev);

    // Statistics about the GPU device
    printf("> GPU device has %d Multi-Processors, "
           "SM %d.%d compute capabilities\n\n",
           deviceProp.multiProcessorCount, deviceProp.major, deviceProp.minor);

    int version = (deviceProp.major * 0x10 + deviceProp.minor);

    unsigned int numThreads = 256;
    unsigned int numBlocks = 64;
    unsigned int numData = 11;
    unsigned int memSize = sizeof(int) * numData;

    //allocate mem for the result on host side
    int *hOData = (int *) malloc(memSize);

    //initialize the memory
    for (unsigned int i = 0; i < numData; i++)
        hOData[i] = 0;

    //To make the AND and XOR tests generate something other than 0...
    hOData[8] = hOData[10] = 0xff;

    // allocate device memory for result
    int *dOData;
    hipMalloc((void **) &dOData, memSize);
    // copy host memory to device to initialize to zero
    hipMemcpy(dOData, hOData, memSize,hipMemcpyHostToDevice);

    // execute the kernel
    hipLaunchKernel(testKernel, dim3(numBlocks), dim3(numThreads), 0, 0, dOData);

    //Copy result from device to host
    hipMemcpy(hOData,dOData, memSize,hipMemcpyDeviceToHost);

    // Compute reference solution
    testResult = computeGold(hOData, numThreads * numBlocks);

    // Cleanup memory
    free(hOData);
    hipFree(dOData);
}

bool run_rnorm4d() {
    double *A, *Ad, *B, *Bd, *C, *Cd, *D, *Dd, *E, *Ed;
    A = new double[N];
    B = new double[N];
    C = new double[N];
    D = new double[N];
    E = new double[N];
    double val = 0.0;
    for (int i = 0; i < N; i++) {
        A[i] = 1.0;
        B[i] = 2.0;
        C[i] = 3.0;
        D[i] = 4.0;
    }
    val = 1 / sqrt(1.0 + 4.0 + 9.0 + 16.0);
    hipMalloc((void**)&Ad, SIZE);
    hipMalloc((void**)&Bd, SIZE);
    hipMalloc((void**)&Cd, SIZE);
    hipMalloc((void**)&Dd, SIZE);
    hipMalloc((void**)&Ed, SIZE);
    hipMemcpy(Ad, A, SIZE, hipMemcpyHostToDevice);
    hipMemcpy(Bd, B, SIZE, hipMemcpyHostToDevice);
    hipMemcpy(Cd, C, SIZE, hipMemcpyHostToDevice);
    hipMemcpy(Dd, D, SIZE, hipMemcpyHostToDevice);
    hipLaunchKernelGGL(test_rnorm4d, dim3(1), dim3(N), 0, 0, Ad, Bd, Cd, Dd, Ed);
    hipMemcpy(E, Ed, SIZE, hipMemcpyDeviceToHost);
    int passed = 0;
    for (int i = 0; i < 512; i++) {
        if (E[i] - val < 0.000001) {
            passed = 1;
        }
    }

    delete[] A;
    delete[] B;
    delete[] C;
    delete[] D;
    delete[] E;
    hipFree(Ad);
    hipFree(Bd);
    hipFree(Cd);
    hipFree(Dd);
    hipFree(Ed);

    if (passed == 1) {
        return true;
    }
    assert(passed == 1);
    return false;
}

void CUDARenderer::windowResize(int width, int height) 
{
	skipStep = true;
	h_info.setWidthHeight(width, height);
	camera.width = h_info.width;
	camera.height = h_info.height;
	setImageInfo(h_info);
	dimBlock = dim3(THREAD_DIM, THREAD_DIM, 1);
	dimGrid = dim3(h_info.width / dimBlock.x + (h_info.width % dimBlock.x > 0), h_info.height / dimBlock.y + (h_info.height % dimBlock.y > 0), 1);

	deleteTexture();
	OGLtexture = Texture2D(GL_TEXTURE_2D);
	initTexture();
}

void CUDARenderer::initCUDA()
{
	gpuErrchk(cudaSetDevice(0));
	gpuErrchk(cudaGLSetGLDevice(0));
	gpuErrchk(cudaMalloc((void **)&d_scene, sizeof(SlowScene)));
	gpuErrchk(cudaMemcpy(d_scene, &h_scene, sizeof(SlowScene), cudaMemcpyHostToDevice));

	setImageInfo(h_info);
	gpuErrchk(cuCtxSetLimit(CU_LIMIT_STACK_SIZE, 1024 * 10));

	dimBlock = dim3(THREAD_DIM, THREAD_DIM, 1);
	dimGrid = dim3(h_info.width / dimBlock.x + (h_info.width % dimBlock.x > 0), h_info.height / dimBlock.y + (h_info.height % dimBlock.y > 0), 1);

	snapshot.init();
}

int main() {
    size_t Nbytes = N * sizeof(int);
    int numDevices = 0;
    int *A_d, *B_d, *C_d, *X_d, *Y_d, *Z_d;
    int *A_h, *B_h, *C_h;
    hipStream_t s;

    HIPCHECK(hipGetDeviceCount(&numDevices));
    if (numDevices > 1) {
        HIPCHECK(hipSetDevice(0));
        unsigned blocks = HipTest::setNumBlocks(blocksPerCU, threadsPerBlock, N);
        HipTest::initArrays(&A_d, &B_d, &C_d, &A_h, &B_h, &C_h, N, false);
        HIPCHECK(hipSetDevice(1));
        HIPCHECK(hipMalloc(&X_d, Nbytes));
        HIPCHECK(hipMalloc(&Y_d, Nbytes));
        HIPCHECK(hipMalloc(&Z_d, Nbytes));


        HIPCHECK(hipSetDevice(0));
        HIPCHECK(hipMemcpy(A_d, A_h, Nbytes, hipMemcpyHostToDevice));
        HIPCHECK(hipMemcpy(B_d, B_h, Nbytes, hipMemcpyHostToDevice));
        hipLaunchKernelGGL(HipTest::vectorADD, dim3(blocks), dim3(threadsPerBlock), 0, 0,
                        static_cast<const int*>(A_d), static_cast<const int*>(B_d), C_d, N);
        HIPCHECK(hipMemcpy(C_h, C_d, Nbytes, hipMemcpyDeviceToHost));
        HIPCHECK(hipDeviceSynchronize());
        HipTest::checkVectorADD(A_h, B_h, C_h, N);

        HIPCHECK(hipSetDevice(1));
        HIPCHECK(hipStreamCreate(&s));
        HIPCHECK(hipMemcpyDtoDAsync((hipDeviceptr_t)X_d, (hipDeviceptr_t)A_d, Nbytes, s));
        HIPCHECK(hipMemcpyDtoDAsync((hipDeviceptr_t)Y_d, (hipDeviceptr_t)B_d, Nbytes, s));

        hipLaunchKernelGGL(HipTest::vectorADD, dim3(blocks), dim3(threadsPerBlock), 0, 0,
                        static_cast<const int*>(X_d), static_cast<const int*>(Y_d), Z_d, N);
        HIPCHECK(hipMemcpyDtoHAsync(C_h, (hipDeviceptr_t)Z_d, Nbytes, s));
        HIPCHECK(hipStreamSynchronize(s));
        HIPCHECK(hipDeviceSynchronize());

        HipTest::checkVectorADD(A_h, B_h, C_h, N);
        HIPCHECK(hipStreamDestroy(s));
        HipTest::freeArrays(A_d, B_d, C_d, A_h, B_h, C_h, false);
        HIPCHECK(hipFree(X_d));
        HIPCHECK(hipFree(Y_d));
        HIPCHECK(hipFree(Z_d));
    }

    passed();
}