File: GB_jit_kernel_cuda_colscale.cu

package info (click to toggle)
suitesparse 1%3A7.10.1%2Bdfsg-1
  • links: PTS, VCS
  • area: main
  • in suites: forky, trixie
  • size: 254,920 kB
  • sloc: ansic: 1,134,743; cpp: 46,133; makefile: 4,875; fortran: 2,087; java: 1,826; sh: 996; ruby: 725; python: 495; asm: 371; sed: 166; awk: 44
file content (104 lines) | stat: -rw-r--r-- 3,333 bytes parent folder | download
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
using namespace cooperative_groups ;

// do not #include functions inside of other functions!
#include "GB_cuda_ek_slice.cuh"

#define log2_chunk_size 10
#define chunk_size 1024

__global__ void GB_cuda_colscale_kernel
(
    GrB_Matrix C,
    GrB_Matrix A,
    GrB_Matrix D
)
{

    const GB_A_TYPE *__restrict__ Ax = (GB_A_TYPE *) A->x ;
    const GB_B_TYPE *__restrict__ Dx = (GB_B_TYPE *) D->x ;
    GB_C_TYPE *__restrict__ Cx = (GB_C_TYPE *) C->x ;

    #if ( GB_A_IS_SPARSE || GB_A_IS_HYPER )
    const GB_Ap_TYPE *__restrict__ Ap = (GB_Ap_TYPE *) A->p ;
        #if ( GB_A_IS_HYPER )
        const GB_Aj_TYPE *__restrict__ Ah = (GB_Aj_TYPE *) A->h ;
        #endif
    #endif

    #if ( GB_A_IS_BITMAP )
    const int8_t *__restrict__ Ab = A->b ;
    #endif

    GB_A_NHELD (anz) ;

    #if (GB_A_IS_BITMAP || GB_A_IS_FULL)
        const int64_t avlen = A->vlen ;
        // bitmap/full case
        int nthreads_in_entire_grid = blockDim.x * gridDim.x ;
        int tid = blockIdx.x * blockDim.x + threadIdx.x ;
        for (int64_t p = tid ; p < anz ; p += nthreads_in_entire_grid)
        {
            if (!GBb_A (Ab, p)) continue ;
            // the pth entry in A is A(i,j) where i = p%avlen and j = p/avlen
            int64_t col_idx = p / avlen ;
    //      int64_t row_idx = p % avlen ;
            GB_DECLAREB (djj) ;
            GB_GETB (djj, Dx, col_idx, ) ;
            GB_DECLAREA (aij) ;
            GB_GETA (aij, Ax, p, ) ;
            // C has same sparsity as A; ewise op code does not change
            GB_EWISEOP (Cx, p, aij, djj, 0, 0) ;
        }

    #else
        const int64_t anvec = A->nvec ;
        // sparse/hypersparse case (cuda_ek_slice only works for sparse/hypersparse)
        for (int64_t pfirst = blockIdx.x << log2_chunk_size ;
                    pfirst < anz ;
                    pfirst += gridDim.x << log2_chunk_size )
            {
                int64_t my_chunk_size, anvec_sub1, kfirst, klast ;
                float slope ;
                GB_cuda_ek_slice_setup (Ap, anvec, anz, pfirst, chunk_size,
                    &kfirst, &klast, &my_chunk_size, &anvec_sub1, &slope) ;

                for (int64_t pdelta = threadIdx.x ; pdelta < my_chunk_size ; pdelta += blockDim.x)
                {
                    int64_t p_final ;
                    int64_t k = GB_cuda_ek_slice_entry (&p_final, pdelta, pfirst, Ap, anvec_sub1, kfirst, slope) ;
                    int64_t j = GBh_A (Ah, k) ;

                    GB_DECLAREB (djj) ;
                    GB_GETB (djj, Dx, j, ) ;
                    GB_DECLAREA (aij) ;
                    GB_GETA (aij, Ax, p_final, ) ;
                    GB_EWISEOP (Cx, p_final, aij, djj, 0, 0) ;
                }
            }
    #endif

    // not needed because threads do entirely independent work:
    // this_thread_block ( ).sync( ) ;
}

extern "C" {
    GB_JIT_CUDA_KERNEL_COLSCALE_PROTO (GB_jit_kernel) ;
}

GB_JIT_CUDA_KERNEL_COLSCALE_PROTO (GB_jit_kernel)
{
    GB_GET_CALLBACKS ;
    ASSERT (GB_JUMBLED_OK (C)) ;
    ASSERT (GB_JUMBLED_OK (A)) ;
    ASSERT (!GB_JUMBLED (D)) ;
    ASSERT (!GB_IS_BITMAP (D)) ;
    ASSERT (!GB_IS_FULL (D)) ;
    ASSERT (!C->iso) ;

    dim3 grid (gridsz) ;
    dim3 block (blocksz) ;
    
    GB_cuda_colscale_kernel <<<grid, block, 0, stream>>> (C, A, D) ;

    return (GrB_SUCCESS) ;
}