统一内存分析失败

Question

我正在Ubuntu16.04上尝试分析cuda代码，它有Cuda 8.0，但是它返回“无法配置应用程序。统一内存分析失败”。我尝试过从终端和Nisght Eclipe进行分析。代码正在编译和运行，但无法对代码进行分析。

密码-

cusparseHandle_t handle;
cusparseCreate(&handle);
cusparseSafeCall(cusparseCreate(&handle));

//set the parameters
const int n_i = 10;
const int d = 18;
const int n_t = 40;
const int n_tau = 2;
const int n_k = 10;

float *data = generate_matrix3_1(d, n_i, n_t);
//float* data = get_data1(d, n_i,n_t);
float* a = generate_matrix3_1(n_i,n_k,n_tau);
float* b = sparse_generate_matrix1(n_k,d,0.5);
float* c = sparse_generate_matrix1(n_k,d,0.5);

float* previous_a = generate_matrix3_1(n_i,n_k,n_tau);
float* previous_b = sparse_generate_matrix1(n_k,d,0.1);
float* previous_c = sparse_generate_matrix1(n_k,d,0.1);

// calculate norm of data
float norm_data = 0;
for (int i = 0; i < n_i; i++)
{
    for (int t = n_tau; t < n_t; t++)
    {
        for (int p = 0; p < d; p++)
        {
            norm_data = norm_data + ((data[p*n_i*n_t + i*n_t + t])*(data[p*n_i*n_t + i*n_t + t]));
        }
    }
}

// set lambda and gamma parameter
float lambda = 0.0001;
float gamma_a = 2;
float gamma_b = 3;
float gamma_c = 4;

float updated_t = 1;
float updated_t1 = 0;

float rel_error = 0;
int loop = 1;
float objective = 0;

// create sparse format for the data
float **h_data = new float*[1];
int **h_data_RowIndices = new int*[1];
int **h_data_ColIndices = new int*[1];
int nnz_data = create_sparse_MY(data,d,n_i*n_t,h_data,h_data_RowIndices,h_data_ColIndices);

// transfer sparse data to device memory
int *d_data_RowIndices;  (cudaMalloc(&d_data_RowIndices, (d+1) * sizeof(int)));
(cudaMemcpy(d_data_RowIndices, h_data_RowIndices[0], (d+1) * sizeof(int), cudaMemcpyHostToDevice));
int *d_data_ColIndices;  (cudaMalloc(&d_data_ColIndices, nnz_data * sizeof(int)));
(cudaMemcpy(d_data_ColIndices, h_data_ColIndices[0], (nnz_data) * sizeof(int), cudaMemcpyHostToDevice));

命令编译代码-

nvcc -lcusparse main.cu -o hello.out

侧写-

-o教授/hello.out

错误-

==13621== NVPROF正在分析过程13621，命令：./hello.out ========错误:统一内存分析失败。

有人能帮我吗？

Answer 1

有同样的误导性错误，只需使用根权限运行分析器，例如sudo nvprof或sudo nvvp。

Answer 2

我也犯了同样的错误。但是，即使我添加了sudo特权，错误仍然存在。终端返回sudo: nvprof: command not found。

试试这个命令，它对我有用。nvprof --unified-memory-profiling off /hello.out

Answer 3

您不需要根访问来修复这个问题。由于您使用的是Cuda 8.0，这应该是可行的。问题在于“iBUS”配置。您所要做的就是删除文件夹/home/user/..config/ibus/bus，问题就会消失。