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mkl_sparse_d_create_csc different definitions

Hi,

I'm having a problem with CSC type sparse matrix generation. The function mkl_sparse_d_create_csc is defined in the intel MKL documentation in the following manner:

sparse_status_t mkl_sparse_d_create_csc (sparse_matrix_t       *A,
                                                                sparse_index_base_t indexing,
                                                                MKL_INT rows,
                                                                MKL_INT cols,
                                                                MKL_INT *cols_start,
                                                                MKL_INT *cols_end,
                                                                MKL_INT *row_indx,
                                                                double *values);

However in the header mkl_spblas.h it is defined differently:

sparse_status_t mkl_sparse_d_create_csc(sparse_matrix_t        *A,
                                                               sparse_index_base_t    indexing, /* indexing: C-style or Fortran-style */
                                                               MKL_INT    rows,
                                                               MKL_INT    cols,
                                                               MKL_INT    *rows_start,
                                                               MKL_INT    *rows_end,
                                                               MKL_INT    *col_indx,
                                                               double        *values );

The definition in the documentation seems to look like a true definition of a CSC type matrix however the definition in the header file looks like a CSR type sparse matrix definition. When I try generating a CSC matrix I get a memory access violation. However I manually checked the input vectors and they are all correctly specified as in the documentation. So I wonder, since the function looks to be defined in the header like a CSR format sparse matrix, should I also give it in this structure?

I'm using MKL version 2019.0.2 for windows.

Thanks for the help,

Adriaan

0 Kudos
17 Replies
Gennady_F_Intel
Moderator
401 Views

yes, you are perfectly right. this issue has been already discussed here and escalated.

Kirill_V_Intel
Employee
401 Views

Hi Adriaan,

As Gennady pointed out, we're aware of the inosistency between the header and the documentation. Please rely on the documentation. However, if you encounter memory access problems when doing so, let us know. In this case we'd ask you to provide some sort of a reproducer (or at least give us more details).

Thanks,
Kirill 

 

401 Views

Thanks for the response Kirill!

I'm writing a function to create a sparse CSC matrix which contains a subset of the columns of another sparse CSC matrix.

The code can be found below. The columns array, input to the function, has three integers specifying the three subsequent column indices I would like to extract.

sparse_matrix_t *column_subset_csc_matrix(sparse_matrix_t X, int *columns)
{
    // setup variables
    sparse_matrix_t *new_matrix = (sparse_matrix_t *)try_alloc(sizeof(sparse_matrix_t));
    sparse_status_t sparse_status;
    sparse_index_base_t indexing_type;
    MKL_INT num_rows, num_columns;
    MKL_INT new_num_rows, new_num_columns;
    MKL_INT *col_starts;
    MKL_INT *col_ends;
    MKL_INT *row_indices;
    double *values;
    MKL_INT *new_col_starts, *new_col_ends;
    int num_non_zero;
    int NUM_POINTS = 3;

    // Obtain the internal CSC data representation

    sparse_status =  mkl_sparse_d_export_csc((const sparse_matrix_t)X, &indexing_type, &num_rows, &num_columns, &col_starts, &col_ends, &row_indices, &values);
    if (sparse_status != SPARSE_STATUS_SUCCESS)
    {
        printf("Extracting internal sparse structure of CSC matrix failed with status: %d\n", sparse_status);
        exit(-1);
    }

    // Allocate space for the new col_start & col_end arrays
    new_col_starts = (MKL_INT *)try_alloc(sizeof(MKL_INT)*NUM_POINTS);
    new_col_ends = (MKL_INT *)try_alloc(sizeof(MKL_INT)*NUM_POINTS);

    // Obtain the new column indices
    for (int i_point = 0; i_point < NUM_POINTS; i_point++)
    {
        new_col_starts[i_point] = col_starts[columns[i_point]];
        new_col_ends[i_point] = col_ends[columns[i_point]];
    }

    // Copy the value array and the row_indices array
    num_non_zero = col_ends[num_columns-1];
    new_num_rows = num_rows;
    new_num_columns = NUM_POINTS;

    // Construct the new sparse matrix
    sparse_status = mkl_sparse_d_create_csc(new_matrix, SPARSE_INDEX_BASE_ZERO, new_num_rows, new_num_columns, new_col_starts, new_col_ends, row_indices, values);
    if (sparse_status != SPARSE_STATUS_SUCCESS)
    {
        printf("Generating 3 column sub matrix failed!!! Status= %d\n", (int)sparse_status);
        exit(-1);
    }
    return new_matrix;

}

 

When calling the mkl_sparse_d_create_csc function I get an access violation error.

 

Any help is very welcome.
Kind regards,

 

Adriaan

may_ka
Beginner
401 Views

Be aware that "create" only creates pointers to the supplied arrays. You can check that out by allocating an array, say "double *b" which you use as "values" array in "create". Then you do an "export" with values now in "a". a[1] will be equal to b[1]. If you now set b[1] to say 5, a[1] will also be 5.

I am using fortran, but if the rule that memory, locally allocated in a function is destroyed when leaving the function, is also valid in c++, your above "create" will create pointers to "new_col_start" and "new_col_end", which are destroyed when leaving function "subset". To avoid this you may have to call "mkl_sparse_copy(new_matrix,new_matrix1)" and return(new_matrix1).

However, in that case "values" and "row_index" are copied as well which may produce a nice memory overhead.

In essence, you have to make sure that the arrays feed into "create" are still allocated after the "create" call. You may achieve this by adding "new_col_end" and "new_col_start" to your function call via "(mkl_int **) new_col_start" and "(mkl_int **) new_col_end"

Kirill_V_Intel
Employee
401 Views

Hi Adriaan,

I have several questions regarding your code. First, col_starts and col_ends which you extract via export_csc store the indices of the nonzero elements at the start and end (-1) of each column. Thus, the values of these arrays are bound to the number of nonzeros in the input (larger) matrix. For example, col_starts[1] will be the index of the nonzero element at the start of the second column. But when you will copy that (imagine columns[0] = 1) into the new_col_starts[0], your new_col_starts[0] will be again something related to the first column of the larger matrix. Not 0 or 1 as it should be depending on the indexing. And this might lead to the memory access error for sure.

Correct me if I got it wrong.

But if I am right, this means that your code is not doing what you want. You need to adjust the col_starts and col_ends arrays for the submatrix.

As a reference, please check out https://software.intel.com/en-us/mkl-developer-reference-fortran-sparse-blas-csc-matrix-storage-form...;

Hope this helps!

Best,
Kirill

may_ka
Beginner
401 Views

While my c++ knowledge is still under construction, according to this your "try_alloc" call inside "column_subset_csc_matrix" puts the arrays on the heap, which are destroyed once the program exits from "column_subset_csc_matrix". From what I understand is that you have to use "new" to get it work.

I wouldn't agree with Kirill about the sub-indices since handle "new_matrix" will contain a pointer to the original "values" and "row_indices" arrays. But be aware that any optimization call will likely produce crap because it may change the order of the elements.

In essence, I still think that your problem boils down to losing memory, and if that is fixed your function should work.

................ Just had a closer look: malloc always put the memory on the heap ........... I am puzzled.

Gennady_F_Intel
Moderator
401 Views

Adriaan, always is better to give the compiled reproducer which we may compile and check the behavior on our side. 

401 Views

Hi Kiril,

Thanks for the reply! However I keep the values array and the row_indices array from the big matrices also for the sub matrix. So the new_col_starts and new_col_ends should still refer to the indices in the big matrix as in my example?

 

Kind regards,

Adriaan

Kirill_V_Intel
Employee
401 Views

Hi Adriaan,

You're providing inconsistent data then. I believe you should provide col_starts, values and row_indices which represent in CSC format your submatrix. If you look at the data you're providing now, your input is very different. Look at the description of what should be in your input arrays in the docs: https://software.intel.com/en-us/mkl-developer-reference-c-mkl-sparse-create-csc

Please, also have a look at the link I gave in my previous post, about the sparse matrix formats.

EDIT: Do you have consecutive columns specified for the submatrix? (I thought the answer is no, in my answers above) If they are consecutive, your call may be valid.
Anyway, it would be much easier for us to see what happens if you provide some working code example

EDIT2: Sorry for my confusion, now I see that the indices are consecutive in your original post.

Best,
Kirill

401 Views

Hi Kirill,

Indeed the columns are consecutive. The problem still persists. I extracted the some values to give an example of where the CSC double matrix creation results in a memory access violation:

int main()
{

    double values[1776] = { -2.377580, 1.611731, 1.050312, -0.078890, 0.506025, -0.423907, -0.660978, -0.359548, 0.877969, 0.508396, -0.250658, -0.812624, -0.690747, 1.146403, -1.029546, 0.884606, -0.112610, 1.386795, 0.901499, 0.488795, 0.665152, 0.550971, 1.391156, 0.175642, 0.910889, 0.707647, 0.713882, 1.185586, -0.630571, 0.322048, -0.125209, -0.699901, -0.513849, 1.570883, 1.261243, 1.205212, -0.742532, -0.191235, 0.451209, 0.394471, 0.734312, -0.055546, -1.903248, -0.241583, 1.039360, -1.645029, 0.197116, 2.369665, -1.404547, -0.592803, -0.069597, 0.142475, 0.340979, 1.393337, -0.053180, 0.106219, -0.086055, 2.181271, 0.238131, -0.816468, 0.668462, -0.819880, 0.384390, 1.120214, 0.168705, -0.305590, -2.778729, -0.605478, 1.493040, 1.519455, 0.427989, 0.917575, 0.995560, 0.558816, 0.935716, 1.221940, -0.315310, 0.315859, -0.185406, -1.127177, 0.699218, 0.269067, -0.663349, 0.047450, 0.512461, -2.421430, -0.244996, 0.935484, -1.173317, -0.467337, -1.289035, -0.053494, -1.615548, 0.180950, -0.978910, -0.418425, 1.059001, 1.781933, -0.129004, -0.562466, -3.407188, 0.763537, 0.778429, -0.381433, 1.053938, 0.075216, 1.690002, -2.113154, -1.274407, 0.459886, -1.651020, 0.668509, -0.616358, -0.726688, -0.665559, 0.145854, 0.977002, 0.659483, 0.489693, 0.346501, -0.323223, -0.658752, -0.106620, -0.084427, -1.123908, -1.213663, -0.034898, -1.384440, -1.257799, 1.751319, 0.529197, -1.454243, 0.460591, -0.091945, -0.238883, -0.103643, -0.970631, 0.212586, 0.495480, 0.837591, -0.561529, 0.504845, 0.069785, 0.514121, -0.288523, 0.547341, 1.448913, 0.723764, 0.313795, -0.437289, 0.122466, -1.060462, -1.304475, -0.195203, 0.531022, -1.490858, -0.808334, 0.422800, 0.897447, 1.971911, 2.339596, 0.029336, -0.080199, 0.328879, 0.196054, -0.454071, -0.243010, -0.797549, -3.985567, 0.430768, -0.716709, -1.297508, -0.999111, 0.342328, 0.287924, -2.164350, -0.493050, -0.040803, -1.232193, 0.707210, 0.580739, 0.009401, 1.183275, -0.952829, 1.469957, 0.482778, 0.168255, -0.166353, 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0.339727, 0.154932, 0.891588, 0.262290, 0.092931, -0.554255, -1.704256, -1.527165, 0.017483, -0.448254, -0.745417, -0.255917, 0.134799, 0.620703, -1.097296, 0.635921, 0.285834, 0.958421, 0.472003, -0.431888, 0.082107, -0.305549, -0.104092, 0.998802, 0.332142, -0.044153, 0.334565, 2.736448, -0.094898, 0.483387, 0.825184, -0.258288, 0.126138, -0.027731, 0.817885, 0.285594, 0.764232, 1.358919, -0.309332, -0.965707, 1.532907, 1.104649, -0.499174, 0.728501, 0.514587, 0.467433, 0.036531, 0.530463, 1.553873, 0.664905, 0.537048, 1.146839, -0.651735, -1.151764, -0.020597, 0.701537, 0.849361, -0.911955, 0.497062, -0.860228, 0.168116, 0.136896, -0.515500, -0.880603, 0.911705, 0.504659, 1.031196, 1.076691, -0.472136, -0.112391, 0.153148, 0.360585, -0.203952, -0.745285, 0.661418, -0.348500, -0.305733, 1.136515, 0.163193, 1.341393, 0.417127, -0.700767, -1.934321, 0.434108, 0.913595, -0.339380, 1.494421, 0.767251, 0.203792, 0.607247, -1.178584, -0.884763, 0.249430, -0.530354, 0.115357, -0.698077, 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216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 1301, 1302, 1303, 1304, 1305, 1306, 1307, 1308, 1309, 1310, 1311, 1312, 1958, 1959, 1960, 1961, 1962, 1963, 1973, 1974, 1975, 1979, 1980, 1981, 1982, 1983, 1984, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2017, 2018, 2019, 2020, 2021, 2022, 2029, 2030, 2031, 2065, 2066, 2067, 2071, 2072, 2073, 2083, 2084, 2085, 2101, 2102, 2103, 2104, 2105, 2106, 2119, 2120, 2121, 4637, 4638, 4639, 4669, 4670, 4671, 4672, 4673, 4674, 4675, 4676, 4677, 4684, 4685, 4686, 4696, 4697, 4698, 4705, 4706, 4707, 4714, 4715, 4716, 4735, 4736, 4737, 4760, 4761, 4762, 4763, 4764, 4765, 66767, 66768, 66769, 66773, 66774, 66775, 66776, 66777, 66778, 66806, 66807, 66808, 66866, 66867, 66868, 66911, 66912, 66913, 66971, 66972, 66973, 67010, 67011, 67012, 67028, 67029, 67030, 67034, 67035, 67036, 67085, 67086, 67087, 67088, 67089, 67090, 67145, 67146, 67147, 67189, 67190, 67191, 67195, 67196, 67197, 67207, 67208, 67209, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 1302, 1303, 1304, 1305, 1306, 1307, 1308, 1309, 1310, 1311, 1312, 1958, 1959, 1960, 1961, 1962, 1963, 1973, 1974, 1975, 1979, 1980, 1981, 1982, 1983, 1984, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2017, 2018, 2019, 2020, 2021, 2022, 2029, 2030, 2031, 2065, 2066, 2067, 2071, 2072, 2073, 2083, 2084, 2085, 2101, 2102, 2103, 2104, 2105, 2106, 2119, 2120, 2121, 4637, 4638, 4639, 4669, 4670, 4671, 4672, 4673, 4674, 4675, 4676, 4677, 4684, 4685, 4686, 4696, 4697, 4698, 4705, 4706, 4707, 4714, 4715, 4716, 4735, 4736, 4737, 4760, 4761, 4762, 4763, 4764, 4765, 66767, 66768, 66769, 66773, 66774, 66775, 66776, 66777, 66778, 66806, 66807, 66808, 66866, 66867, 66868, 66911, 66912, 66913, 66971, 66972, 66973, 67010, 67011, 67012, 67028, 67029, 67030, 67034, 67035, 67036, 67085, 67086, 67087, 67088, 67089, 67090, 67145, 67146, 67147, 67189, 67190, 67191, 67195, 67196, 67197, 67207, 67208, 67209, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 1303, 1304, 1305, 1306, 1307, 1308, 1309, 1310, 1311, 1312, 1958, 1959, 1960, 1961, 1962, 1963, 1973, 1974, 1975, 1979, 1980, 1981, 1982, 1983, 1984, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2017, 2018, 2019, 2020, 2021, 2022, 2029, 2030, 2031, 2065, 2066, 2067, 2071, 2072, 2073, 2083, 2084, 2085, 2101, 2102, 2103, 2104, 2105, 2106, 2119, 2120, 2121, 4637, 4638, 4639, 4669, 4670, 4671, 4672, 4673, 4674, 4675, 4676, 4677, 4684, 4685, 4686, 4696, 4697, 4698, 4705, 4706, 4707, 4714, 4715, 4716, 4735, 4736, 4737, 4760, 4761, 4762, 4763, 4764, 4765, 66767, 66768, 66769, 66773, 66774, 66775, 66776, 66777, 66778, 66806, 66807, 66808, 66866, 66867, 66868, 66911, 66912, 66913, 66971, 66972, 66973, 67010, 67011, 67012, 67028, 67029, 67030, 67034, 67035, 67036, 67085, 67086, 67087, 67088, 67089, 67090, 67145, 67146, 67147, 67189, 67190, 67191, 67195, 67196, 67197, 67207, 67208, 67209};
    MKL_INT col_begin[3] = {0, 593, 1185};
    MKL_INT col_end[3] = {593, 1185, 1776};
    MKL_INT num_cols = 3;
    MKL_INT num_rows = 67874;
    sparse_index_base_t  indexing_type = SPARSE_INDEX_BASE_ZERO;
    sparse_status_t status;
    sparse_matrix_t X;

    status = mkl_sparse_d_create_csc(&X, indexing_type, num_rows, num_cols, col_begin, col_end, row_ind, values);
    if (status != SPARSE_STATUS_SUCCESS)
    {
        return -1;
    }
}

 

Thanks for the help!

Adriaan

Gennady_F_Intel
Moderator
401 Views

Thanks for report. Yes, the Exception problem is reproduced on our side and will be investigated.

401 Views

Hi is there an update on this issue?

Kind regards,
Adriaan

Gennady_F_Intel
Moderator
401 Views

Hello. We are planning to release the fix of this problem into the next version of MKL. This thread will be updated as soon as this version will be published.

b_shier
Beginner
275 Views

Hello,

Is there any updated information on when the fix will be available?

Thanks,

Brian

Gennady_F_Intel
Moderator
260 Views

You may check the problem with the current (latest)version of MKL 2021.

b_shier
Beginner
245 Views

Thanks. I have confirmed the fix in MKL 2021.1.

Brian

Gennady_F_Intel
Moderator
230 Views

Thanks for the update. This issue has been resolved and we will no longer respond to this thread. If you require additional assistance from Intel, please start a new thread. Any further interaction in this thread will be considered community only.

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