Wraping a MKL handle in julia

General Usage
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9

To follow up on this, you can create p as below using Ref and avoid creation of an array.

julia> p = Ref(Ptr{Cvoid}(0))
Base.RefValue{Ptr{Nothing}}(Ptr{Nothing} @0x0000000000000000)

julia> p[]
Ptr{Nothing} @0x0000000000000000

julia> ccall((:mkl_sparse_d_create_csc, libmkl_rt), Cint, (Ref{Ptr{Cvoid}}, sparse_index_base_t, Int64, Int64, Ptr{Int64}, Ptr{Int64}, Ptr{Int64}, Ptr{Cdouble}),           p, SPARSE_INDEX_BASE_ONE, m.m, m.n, m.colptr, pointer(m.colptr, 2), m.rowval, m.nzval)0

julia> p[]
Ptr{Nothing} @0x0000000004965000

julia> B = Matrix(Float64.(I(10)));

julia> C = zeros(Float64, 10, 10);

julia> ccall((:mkl_sparse_d_mm, libmkl_rt), sparse_status_t, (sparse_operation_t, Cdouble, Ptr{Cvoid}, matrix_descr, sparse_layout_t, Ptr{Cdouble}, BlasInt, BlasInt, Cdouble, Ptr{Cdouble}, BlasInt, BlasInt), SPARSE_OPERATION_NON_TRANSPOSE, 1.0, p[], matrix_descr(SPARSE_MATRIX_TYPE_GENERAL, SPARSE_FILL_MODE_FULL, SPARSE_DIAG_NON_UNIT), SPARSE_LAYOUT_COLUMN_MAJOR, B, 10, 10, 0.0, C, 10, 10)
SPARSE_STATUS_SUCCESS::sparse_status_t = 0

julia> C
10×10 Array{Float64,2}:
 0.0  0.0  0.0  0.0  1.0  0.0  0.0  0.0  0.0  0.0
 0.0  1.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0  1.0  0.0  0.0  0.0  0.0
 0.0  0.0  1.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0  0.0
 1.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0  0.0  0.0
 0.0  0.0  0.0  0.0  1.0  0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0  0.0  1.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0

The various enums are lightly modified code from mkl_spblas.h

using LinearAlgebra
using MKL_jll
using Base.Enums
using LinearAlgebra: BlasInt

function __init__()
    ccall((:MKL_Set_Interface_Layer, libmkl_rt), Cint, (Cint,), Base.USE_BLAS64 ? 1 : 0)
end

# Basic types and constants for inspector-executor SpBLAS API

@enum(
    sparse_status_t,
    SPARSE_STATUS_SUCCESS           = 0,
    SPARSE_STATUS_NOT_INITIALIZED   = 1,
    SPARSE_STATUS_ALLOC_FAILED      = 2,
    SPARSE_STATUS_INVALID_VALUE     = 3,
    SPARSE_STATUS_EXECUTION_FAILED  = 4,
    SPARSE_STATUS_INTERNAL_ERROR    = 5,
    SPARSE_STATUS_NOT_SUPPORTED     = 6
)

@enum(
    sparse_operation_t,
    SPARSE_OPERATION_NON_TRANSPOSE       = 10,
    SPARSE_OPERATION_TRANSPOSE           = 11,
    SPARSE_OPERATION_CONJUGATE_TRANSPOSE = 12
)

@enum(
    sparse_matrix_type_t,
    SPARSE_MATRIX_TYPE_GENERAL            = 20,
    SPARSE_MATRIX_TYPE_SYMMETRIC          = 21,
    SPARSE_MATRIX_TYPE_HERMITIAN          = 22,
    SPARSE_MATRIX_TYPE_TRIANGULAR         = 23,
    SPARSE_MATRIX_TYPE_DIAGONAL           = 24,
    SPARSE_MATRIX_TYPE_BLOCK_TRIANGULAR   = 25,
    SPARSE_MATRIX_TYPE_BLOCK_DIAGONAL     = 26
)

@enum(
    sparse_index_base_t,
    SPARSE_INDEX_BASE_ZERO    = 0,
    SPARSE_INDEX_BASE_ONE     = 1
)

@enum(
    sparse_fill_mode_t,
    SPARSE_FILL_MODE_LOWER  = 40,
    SPARSE_FILL_MODE_UPPER  = 41,
    SPARSE_FILL_MODE_FULL   = 42
)

@enum(
    sparse_diag_type_t,
    SPARSE_DIAG_NON_UNIT    = 50, 
    SPARSE_DIAG_UNIT        = 51
)

@enum(
    sparse_layout_t,
    SPARSE_LAYOUT_ROW_MAJOR    = 101,
    SPARSE_LAYOUT_COLUMN_MAJOR = 102
)

@enum(
    verbose_mode_t,
    SPARSE_VERBOSE_OFF      = 70,
    SPARSE_VERBOSE_BASIC    = 71,
    SPARSE_VERBOSE_EXTENDED = 72
)

@enum(
    sparse_memory_usage_t,
    SPARSE_MEMORY_NONE          = 80,
    SPARSE_MEMORY_AGGRESSIVE    = 81  
)

@enum(
    sparse_request_t,
    SPARSE_STAGE_FULL_MULT            = 90,
    SPARSE_STAGE_NNZ_COUNT            = 91,
    SPARSE_STAGE_FINALIZE_MULT        = 92,
    SPARSE_STAGE_FULL_MULT_NO_VAL     = 93,
    SPARSE_STAGE_FINALIZE_MULT_NO_VAL = 94
)

struct matrix_descr
    type::sparse_matrix_type_t
    mode::sparse_fill_mode_t
    diag::sparse_diag_type_t
end
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