Rename 2_Advanced to 7_Advanced

Change-Id: I51e5fa7f4c1dbf467f2d7182ec69d12d5fe548d0


[ROCm/hip-tests commit: 6ad8ac5d95]

projects/hip-tests/samples/7_Advanced/hipblas_saxpy/saxpy.cublas.cpp

@@ -0,0 +1,94 @@
+
+#include <random>
+#include <algorithm>
+#include <iostream>
+#include <cmath>
+
+// header file for the GPU API
+#include <cuda_runtime.h>
+#include <cublas_v2.h>
+
+#define N  (1024 * 500)
+
+#define CHECK(cmd) \
+{\
+    cudaError_t error  = cmd;   \
+    if (error != cudaSuccess) { \
+      fprintf(stderr, "error: '%s'(%d) at %s:%d\n", cudaGetErrorString(error), error,__FILE__, __LINE__); \
+      exit(EXIT_FAILURE);\
+    }\
+}
+
+#define CHECK_BLAS(cmd)			\
+{\
+    cublasStatus_t error  = cmd;\
+    if (error != CUBLAS_STATUS_SUCCESS) { \
+      fprintf(stderr, "error: (%d) at %s:%d\n", error,__FILE__, __LINE__); \
+      exit(EXIT_FAILURE);\
+    }\
+}
+
+int main() {
+
+  const float a = 100.0f;
+  float x[N];
+  float y[N], y_cpu_res[N], y_gpu_res[N];
+
+  // initialize the input data
+  std::default_random_engine random_gen;
+  std::uniform_real_distribution<float> distribution(-N, N);
+  std::generate_n(x, N, [&]() { return distribution(random_gen); });
+  std::generate_n(y, N, [&]() { return distribution(random_gen); });
+  std::copy_n(y, N, y_cpu_res);
+
+  // Explicit GPU code:  
+
+  size_t Nbytes = N*sizeof(float);
+  float *x_gpu, *y_gpu;
+
+  cublasHandle_t handle;
+
+  cudaDeviceProp props;
+  CHECK(cudaGetDeviceProperties(&props, 0/*deviceID*/));
+  printf ("info: running on device %s\n", props.name);
+
+  printf ("info: allocate host mem (%6.2f MB)\n", 2*Nbytes/1024.0/1024.0);
+  printf ("info: allocate device mem (%6.2f MB)\n", 2*Nbytes/1024.0/1024.0);
+  CHECK(cudaMalloc(&x_gpu, Nbytes));
+  CHECK(cudaMalloc(&y_gpu, Nbytes));
+
+  // Initialize the blas library
+  CHECK_BLAS ( cublasCreate(&handle));
+
+  // copy n elements from a vector in host memory space to a vector in GPU memory space
+  printf ("info: copy Host2Device\n");
+  CHECK_BLAS ( cublasSetVector(N, sizeof(*x), x, 1, x_gpu, 1));
+  CHECK_BLAS ( cublasSetVector(N, sizeof(*y), y, 1, y_gpu, 1));
+
+  printf ("info: launch 'saxpy' kernel\n");
+  CHECK_BLAS ( cublasSaxpy(handle, N, &a, x_gpu, 1, y_gpu, 1));  
+
+  cudaDeviceSynchronize();
+
+  printf ("info: copy Device2Host\n");
+  CHECK_BLAS ( cublasGetVector(N, sizeof(*y_gpu_res), y_gpu, 1, y_gpu_res, 1)); 
+
+  // CPU implementation of saxpy
+  for (int i = 0; i < N; i++) {
+    y_cpu_res[i] = a * x[i] + y[i];
+  }
+
+  // verify the results
+  int errors = 0;
+  for (int i = 0; i < N; i++) {
+    if (fabs(y_cpu_res[i] - y_gpu_res[i]) > fabs(y_cpu_res[i] * 0.0001f))
+      errors++;
+  }
+  std::cout << errors << " errors" << std::endl;
+
+  CHECK( cudaFree(x_gpu));
+  CHECK( cudaFree(y_gpu));
+  CHECK_BLAS( cublasDestroy(handle));
+
+  return errors;
+}