Add simple hipblas saxpy sample
Change-Id: I67ae83e1e5397d5191a3c644aba068f06ff97830
[ROCm/hip commit: d192976b00]
Этот коммит содержится в:
Maneesh Gupta
@@ -0,0 +1,34 @@
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HIP_PATH?= $(wildcard /opt/rocm/hip)
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ifeq (,$(HIP_PATH))
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HIP_PATH=../../..
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endif
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HIPCC=$(HIP_PATH)/bin/hipcc
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HIPCC_FLAGS += -std=c++11
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HIP_PLATFORM=$(shell $(HIP_PATH)/bin/hipconfig --platform)
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ifeq (${HIP_PLATFORM}, nvcc)
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LIBS = -lcublas
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endif
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ifeq (${HIP_PLATFORM}, hcc)
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HCBLAS_ROOT?= $(wildcard /opt/rocm/hcblas)
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HIPCC_FLAGS += -stdlib=libc++ -I$(HCBLAS_ROOT)/include
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LIBS = -L$(HCBLAS_ROOT)/lib -lhcblas
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endif
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all: saxpy.hipblas.out
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saxpy.cublas.out : saxpy.cublas.cpp
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nvcc -std=c++11 -I$(CUDA_HOME)/include saxpy.cublas.cpp -o $@ -L$(CUDA_HOME)/lib64 -lcublas
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# $HIPBLAS_ROOT/bin/hipifyblas ./saxpy.cublas.cpp > ./saxpy.hipblas.cpp
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# Then review & finish port in saxpy.hipblas.cpp
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saxpy.hipblasref.o: saxpy.hipblasref.cpp
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$(HIPCC) $(HIPCC_FLAGS) -c $< -o $@
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saxpy.hipblas.out: saxpy.hipblasref.o
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$(HIPCC) $< -o $@ $(LIBS)
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clean:
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rm -f *.o *.out
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@@ -0,0 +1,94 @@
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#include <random>
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#include <algorithm>
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#include <iostream>
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#include <cmath>
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// header file for the GPU API
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#include <cuda_runtime.h>
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#include <cublas_v2.h>
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#define N (1024 * 500)
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#define CHECK(cmd) \
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{\
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cudaError_t error = cmd; \
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if (error != cudaSuccess) { \
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fprintf(stderr, "error: '%s'(%d) at %s:%d\n", cudaGetErrorString(error), error,__FILE__, __LINE__); \
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exit(EXIT_FAILURE);\
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}\
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}
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#define CHECK_BLAS(cmd) \
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{\
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cublasStatus_t error = cmd;\
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if (error != CUBLAS_STATUS_SUCCESS) { \
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fprintf(stderr, "error: (%d) at %s:%d\n", error,__FILE__, __LINE__); \
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exit(EXIT_FAILURE);\
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}\
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}
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int main() {
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const float a = 100.0f;
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float x[N];
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float y[N], y_cpu_res[N], y_gpu_res[N];
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// initialize the input data
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std::default_random_engine random_gen;
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std::uniform_real_distribution<float> distribution(-N, N);
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std::generate_n(x, N, [&]() { return distribution(random_gen); });
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std::generate_n(y, N, [&]() { return distribution(random_gen); });
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std::copy_n(y, N, y_cpu_res);
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// Explicit GPU code:
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size_t Nbytes = N*sizeof(float);
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float *x_gpu, *y_gpu;
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cublasHandle_t handle;
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cudaDeviceProp props;
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CHECK(cudaGetDeviceProperties(&props, 0/*deviceID*/));
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printf ("info: running on device %s\n", props.name);
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printf ("info: allocate host mem (%6.2f MB)\n", 2*Nbytes/1024.0/1024.0);
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printf ("info: allocate device mem (%6.2f MB)\n", 2*Nbytes/1024.0/1024.0);
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CHECK(cudaMalloc(&x_gpu, Nbytes));
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CHECK(cudaMalloc(&y_gpu, Nbytes));
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// Initialize the blas library
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CHECK_BLAS ( cublasCreate(&handle));
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// copy n elements from a vector in host memory space to a vector in GPU memory space
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printf ("info: copy Host2Device\n");
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CHECK_BLAS ( cublasSetVector(N, sizeof(*x), x, 1, x_gpu, 1));
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CHECK_BLAS ( cublasSetVector(N, sizeof(*y), y, 1, y_gpu, 1));
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printf ("info: launch 'saxpy' kernel\n");
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CHECK_BLAS ( cublasSaxpy(handle, N, &a, x_gpu, 1, y_gpu, 1));
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cudaDeviceSynchronize();
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printf ("info: copy Device2Host\n");
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CHECK_BLAS ( cublasGetVector(N, sizeof(*y_gpu_res), y_gpu, 1, y_gpu_res, 1));
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// CPU implementation of saxpy
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for (int i = 0; i < N; i++) {
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y_cpu_res[i] = a * x[i] + y[i];
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}
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// verify the results
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int errors = 0;
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for (int i = 0; i < N; i++) {
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if (fabs(y_cpu_res[i] - y_gpu_res[i]) > fabs(y_cpu_res[i] * 0.0001f))
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errors++;
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}
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std::cout << errors << " errors" << std::endl;
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CHECK( cudaFree(x_gpu));
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CHECK( cudaFree(y_gpu));
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CHECK_BLAS( cublasDestroy(handle));
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return errors;
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}
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@@ -0,0 +1,94 @@
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#include <random>
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#include <algorithm>
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#include <iostream>
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#include <cmath>
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// header file for the GPU API
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#include <hip_runtime.h>
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#include <hipblas.h>
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#define N (1024 * 500)
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#define CHECK(cmd) \
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{\
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hipError_t error = cmd; \
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if (error != hipSuccess) { \
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fprintf(stderr, "error: '%s'(%d) at %s:%d\n", hipGetErrorString(error), error,__FILE__, __LINE__); \
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exit(EXIT_FAILURE);\
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}\
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}
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#define CHECK_BLAS(cmd) \
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{\
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hipblasStatus_t error = cmd;\
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if (error != HIPBLAS_STATUS_SUCCESS) { \
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fprintf(stderr, "error: (%d) at %s:%d\n", error,__FILE__, __LINE__); \
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exit(EXIT_FAILURE);\
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}\
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}
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int main() {
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const float a = 100.0f;
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float x[N];
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float y[N], y_cpu_res[N], y_gpu_res[N];
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// initialize the input data
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std::default_random_engine random_gen;
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std::uniform_real_distribution<float> distribution(-N, N);
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std::generate_n(x, N, [&]() { return distribution(random_gen); });
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std::generate_n(y, N, [&]() { return distribution(random_gen); });
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std::copy_n(y, N, y_cpu_res);
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// Explicit GPU code:
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size_t Nbytes = N*sizeof(float);
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float *x_gpu, *y_gpu;
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hipblasHandle_t handle;
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hipDeviceProp_t props;
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CHECK(hipGetDeviceProperties(&props, 0/*deviceID*/));
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printf ("info: running on device %s\n", props.name);
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printf ("info: allocate host mem (%6.2f MB)\n", 2*Nbytes/1024.0/1024.0);
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printf ("info: allocate device mem (%6.2f MB)\n", 2*Nbytes/1024.0/1024.0);
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CHECK(hipMalloc(&x_gpu, Nbytes));
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CHECK(hipMalloc(&y_gpu, Nbytes));
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// Initialize the blas library
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CHECK_BLAS ( hipblasCreate(&handle));
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// copy n elements from a vector in host memory space to a vector in GPU memory space
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printf ("info: copy Host2Device\n");
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CHECK_BLAS ( hipblasSetVector(N, sizeof(*x), x, 1, x_gpu, 1));
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CHECK_BLAS ( hipblasSetVector(N, sizeof(*y), y, 1, y_gpu, 1));
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printf ("info: launch 'saxpy' kernel\n");
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CHECK_BLAS ( hipblasSaxpy(handle, N, &a, x_gpu, 1, y_gpu, 1));
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hipDeviceSynchronize();
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printf ("info: copy Device2Host\n");
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CHECK_BLAS ( hipblasGetVector(N, sizeof(*y_gpu_res), y_gpu, 1, y_gpu_res, 1));
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// CPU implementation of saxpy
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for (int i = 0; i < N; i++) {
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y_cpu_res[i] = a * x[i] + y[i];
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}
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// verify the results
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int errors = 0;
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for (int i = 0; i < N; i++) {
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if (fabs(y_cpu_res[i] - y_gpu_res[i]) > fabs(y_cpu_res[i] * 0.0001f))
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errors++;
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}
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std::cout << errors << " errors" << std::endl;
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CHECK( hipFree(x_gpu));
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CHECK( hipFree(y_gpu));
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CHECK_BLAS( hipblasDestroy(handle));
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return errors;
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}
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