[HIPIFY][tests] Add reverse engineered HIP sample "stream"

+ Add additional checks for extern __shared__ due to [#1109]


[ROCm/clr commit: 7cc12df514]

projects/clr/hipamd/tests/hipify-clang/unit_tests/samples/2_Cookbook/0_MatrixTranspose/MatrixTranspose.cpp

@@ -1,6 +1,6 @@
 // RUN: %run_test hipify "%s" "%t" %hipify_args %clang_args
 /*
-Copyright (c) 2015-2019 Advanced Micro Devices, Inc. All rights reserved.
+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

projects/clr/hipamd/tests/hipify-clang/unit_tests/samples/2_Cookbook/7_streams/stream.cpp

@@ -0,0 +1,153 @@
+// 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>
+
+#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;
+
+__global__ void matrixTranspose_static_shared(float* out, float* in,
+                                              const int width) {
+    // CHECK-NOT: HIP_DYNAMIC_SHARED(int, 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(int, sharedMem)
+    extern __shared__ int 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];
+}
+
+void MultipleStream(float** data, float* randArray, float** gpuTransposeMatrix,
+                    float** TransposeMatrix, int width) {
+    const int num_streams = 2;
+    // CHECK: hipStream_t streams[num_streams];
+    cudaStream_t streams[num_streams];
+
+    // CHECK: for (int i = 0; i < num_streams; i++) hipStreamCreate(&streams[i]);
+    for (int i = 0; i < num_streams; i++) cudaStreamCreate(&streams[i]);
+
+    for (int i = 0; i < num_streams; i++) {
+        // CHECK: hipMalloc((void**)&data[i], NUM * sizeof(float));
+        cudaMalloc((void**)&data[i], NUM * sizeof(float));
+        // CHECK: hipMemcpyAsync(data[i], randArray, NUM * sizeof(float), hipMemcpyHostToDevice, streams[i]);
+        cudaMemcpyAsync(data[i], randArray, NUM * sizeof(float), cudaMemcpyHostToDevice, streams[i]);
+    }
+
+    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, streams[0], gpuTransposeMatrix[0], data[0], width);
+    matrixTranspose_static_shared <<<dimGrid, dimBlock, 0, streams[0]>>>(gpuTransposeMatrix[0], data[0], width);
+    // CHECK: hipLaunchKernelGGL(matrixTranspose_dynamic_shared, dim3(dimGrid), dim3(dimBlock), 0, streams[1], gpuTransposeMatrix[1], data[1], width);
+    matrixTranspose_dynamic_shared <<<dimGrid, dimBlock, 0, streams[1]>>>(gpuTransposeMatrix[1], data[1], width);
+
+    for (int i = 0; i < num_streams; i++)
+        // CHECK: hipMemcpyAsync(TransposeMatrix[i], gpuTransposeMatrix[i], NUM * sizeof(float), hipMemcpyDeviceToHost, streams[i]);
+        cudaMemcpyAsync(TransposeMatrix[i], gpuTransposeMatrix[i], NUM * sizeof(float), cudaMemcpyDeviceToHost, streams[i]);
+}
+
+int main() {
+    // CHECK: hipSetDevice(0);
+    cudaSetDevice(0);
+
+    float *data[2], *TransposeMatrix[2], *gpuTransposeMatrix[2], *randArray;
+
+    int width = WIDTH;
+
+    randArray = (float*)malloc(NUM * sizeof(float));
+
+    TransposeMatrix[0] = (float*)malloc(NUM * sizeof(float));
+    TransposeMatrix[1] = (float*)malloc(NUM * sizeof(float));
+
+    // CHECK: hipMalloc((void**)&gpuTransposeMatrix[0], NUM * sizeof(float));
+    cudaMalloc((void**)&gpuTransposeMatrix[0], NUM * sizeof(float));
+    // CHECK: hipMalloc((void**)&gpuTransposeMatrix[1], NUM * sizeof(float));
+    cudaMalloc((void**)&gpuTransposeMatrix[1], NUM * sizeof(float));
+
+    for (int i = 0; i < NUM; i++) {
+        randArray[i] = (float)i * 1.0f;
+    }
+
+    MultipleStream(data, randArray, gpuTransposeMatrix, TransposeMatrix, width);
+
+    // CHECK: hipDeviceSynchronize();
+    cudaDeviceSynchronize();
+
+    // verify the results
+    int errors = 0;
+    double eps = 1.0E-6;
+    for (int i = 0; i < NUM; i++) {
+        if (std::abs(TransposeMatrix[0][i] - TransposeMatrix[1][i]) > eps) {
+            printf("%d stream0: %f stream1  %f\n", i, TransposeMatrix[0][i], TransposeMatrix[1][i]);
+            errors++;
+        }
+    }
+    if (errors != 0) {
+        printf("FAILED: %d errors\n", errors);
+    } else {
+        printf("stream 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: hipDeviceReset();
+    cudaDeviceReset();
+    return 0;
+}