Bitwise reproducibility

Contents

Bitwise reproducibility#

Some routines do not produce deterministic results from run to run. Typically this is the case when HIP atomics are used. This page catalogues the run to run reproducibility of each routine.

Sparse Level 1 Functions#

Function name	yes	no
`rocsparse_Xaxpyi()`	x
`rocsparse_Xdoti()`	x
`rocsparse_Xdotci()`	x
`rocsparse_Xgthr()`	x
`rocsparse_Xgthrz()`	x
`rocsparse_Xroti()`	x
`rocsparse_Xsctr()`	x

Sparse Level 2 Functions#

Function name	yes	no
`rocsparse_Xbsrmv_ex_analysis()`	x
`rocsparse_bsrmv_ex_clear()`	x
`rocsparse_Xbsrmv_ex()`	x
`rocsparse_Xbsrmv()`	x
`rocsparse_Xbsrxmv()`	x
`rocsparse_Xbsrsv_buffer_size()`	x
`rocsparse_Xbsrsv_analysis()`		x
`rocsparse_bsrsv_zero_pivot()`	x
`rocsparse_bsrsv_clear()`	x
`rocsparse_Xbsrsv_solve()`		x
`rocsparse_Xcsrmv_analysis()`	x
`rocsparse_csrmv_clear()`	x
`rocsparse_Xcsrsv_buffer_size()`	x
`rocsparse_Xcsrsv_analysis()`		x
`rocsparse_csrsv_zero_pivot()`	x
`rocsparse_csrsv_clear()`	x
`rocsparse_Xcsrsv_solve()`		x
`rocsparse_Xcsritsv_buffer_size()`	x
`rocsparse_Xcsritsv_analysis()`		x
`rocsparse_csritsv_zero_pivot()`	x
`rocsparse_csritsv_clear()`	x
`rocsparse_Xcsritsv_solve()`		x
`rocsparse_Xgemvi_buffer_size()`	x
`rocsparse_Xgemvi()`	x

The reproducibility of rocsparse_Xbsrmv_ex(), rocsparse_Xbsrmv(), rocsparse_Xbsrxmv(), rocsparse_Xcoomv(), rocsparse_Xcsrmv(), rocsparse_Xellmv(), rocsparse_Xhybmv(), and rocsparse_Xgebsrmv() is more complicated depending on whether A is transposed or not. See the below chart to determine whether these routines are deterministic.

Routine	A non-transpose		A transpose
Routine	Yes	No	Yes	No
rocsparse_Xbsrmv_ex	x		N/A	N/A
rocsparse_Xbsrmv	x		N/A	N/A
rocsparse_Xbsrxmv	x		N/A	N/A
rocsparse_Xcoomv	x			x
rocsparse_Xcsrmv	x			x
rocsparse_Xcsrmv (info != NULL)		x		x
rocsparse_Xellmv	x			x
rocsparse_Xhybmv	x			x
rocsparse_Xgebsrmv	x		N/A	N/A

Sparse Level 3 Functions#

Function name	yes	no
`rocsparse_Xcsrsm_buffer_size()`	x
`rocsparse_Xcsrsm_analysis()`		x
`rocsparse_csrsm_zero_pivot()`	x
`rocsparse_csrsm_clear()`	x
`rocsparse_Xcsrsm_solve()`		x
`rocsparse_Xbsrsm_buffer_size()`	x
`rocsparse_Xbsrsm_analysis()`		x
`rocsparse_bsrsm_zero_pivot()`	x
`rocsparse_bsrsm_clear()`	x
`rocsparse_Xbsrsm_solve()`		x
`rocsparse_Xgemmi()`	x

The reproducibility of rocsparse_Xbsrmm(), rocsparse_Xgebsrmm(), and rocsparse_Xcsrmm() is more complicated depending on whether A is transposed or not. See the below chart to determine whether these routines are deterministic.

Routine	A non-transpose		A transpose
Routine	Yes	No	Yes	No
rocsparse_Xbsrmm	x		N/A	N/A
rocsparse_Xgebsrmm	x		N/A	N/A
rocsparse_Xcsrmm	x			x

Sparse Extra Functions#

Function name	yes	no
`rocsparse_bsrgeam_nnzb()`	x
`rocsparse_Xbsrgeam()`	x
`rocsparse_Xbsrgemm_buffer_size()`	x
`rocsparse_bsrgemm_nnzb()`	x
`rocsparse_Xbsrgemm()`	x
`rocsparse_csrgeam_nnz()`	x
`rocsparse_Xcsrgeam()`	x
`rocsparse_Xcsrgemm_buffer_size()`	x
`rocsparse_csrgemm_nnz()`		x
`rocsparse_csrgemm_symbolic()`		x
`rocsparse_Xcsrgemm()`		x
`rocsparse_Xcsrgemm_numeric()`		x

Preconditioner Functions#

Function name	yes	no
`rocsparse_Xbsric0_buffer_size()`	x
`rocsparse_Xbsric0_analysis()`		x
`rocsparse_bsric0_zero_pivot()`	x
`rocsparse_bsric0_clear()`	x
`rocsparse_Xbsric0()`		x
`rocsparse_Xbsrilu0_buffer_size()`	x
`rocsparse_Xbsrilu0_analysis()`		x
`rocsparse_bsrilu0_zero_pivot()`	x
`rocsparse_Xbsrilu0_numeric_boost()`		x
`rocsparse_bsrilu0_clear()`	x
`rocsparse_Xbsrilu0()`		x
`rocsparse_Xcsric0_buffer_size()`	x
`rocsparse_Xcsric0_analysis()`		x
`rocsparse_csric0_zero_pivot()`	x
`rocsparse_csric0_clear()`	x
`rocsparse_Xcsric0()`		x
`rocsparse_Xcsrilu0_buffer_size()`	x
`rocsparse_Xcsrilu0_numeric_boost()`		x
`rocsparse_Xcsrilu0_analysis()`		x
`rocsparse_csrilu0_zero_pivot()`	x
`rocsparse_csrilu0_clear()`	x
`rocsparse_Xcsrilu0()`		x
`rocsparse_csritilu0_buffer_size()`	x
`rocsparse_csritilu0_preprocess()`		x
`rocsparse_Xcsritilu0_compute()`		x
`rocsparse_Xcsritilu0_history()`		x
`rocsparse_Xgtsv_buffer_size()`	x
`rocsparse_Xgtsv()`	x
`rocsparse_Xgtsv_no_pivot_buffer_size()`	x
`rocsparse_Xgtsv_no_pivot()`	x
`rocsparse_Xgtsv_no_pivot_strided_batch_buffer_size()`	x
`rocsparse_Xgtsv_no_pivot_strided_batch()`	x
`rocsparse_Xgtsv_interleaved_batch_buffer_size()`	x
`rocsparse_Xgtsv_interleaved_batch()`	x
`rocsparse_Xgpsv_interleaved_batch_buffer_size()`	x
`rocsparse_Xgpsv_interleaved_batch()`	x

Conversion Functions#

Function name	yes	no
`rocsparse_csr2coo()`	x
`rocsparse_csr2csc_buffer_size()`	x
`rocsparse_Xcsr2csc()`	x
`rocsparse_Xgebsr2gebsc_buffer_size()`	x
`rocsparse_Xgebsr2gebsc()`	x
`rocsparse_csr2ell_width()`	x
`rocsparse_Xcsr2ell()`	x
`rocsparse_Xcsr2hyb()`	x
`rocsparse_csr2bsr_nnz()`	x
`rocsparse_Xcsr2bsr()`	x
`rocsparse_csr2gebsr_nnz()`	x
`rocsparse_Xcsr2gebsr_buffer_size()`	x
`rocsparse_Xcsr2gebsr()`	x
`rocsparse_coo2csr()`	x
`rocsparse_ell2csr_nnz()`	x
`rocsparse_Xell2csr()`	x
`rocsparse_hyb2csr_buffer_size()`	x
`rocsparse_Xhyb2csr()`	x
`rocsparse_Xbsr2csr()`	x
`rocsparse_Xgebsr2csr()`	x
`rocsparse_Xgebsr2gebsr_buffer_size()`	x
`rocsparse_gebsr2gebsr_nnz()`	x
`rocsparse_Xgebsr2gebsr()`	x
`rocsparse_Xcsr2csr_compress()`	x
`rocsparse_create_identity_permutation()`	x
`rocsparse_inverse_permutation()`	x
`rocsparse_cscsort_buffer_size()`	x
`rocsparse_cscsort()`	x
`rocsparse_csrsort_buffer_size()`	x
`rocsparse_csrsort()`	x
`rocsparse_coosort_buffer_size()`	x
`rocsparse_coosort_by_row()`	x
`rocsparse_coosort_by_column()`	x
`rocsparse_Xdense2csr()`	x
`rocsparse_Xdense2csc()`	x
`rocsparse_Xdense2coo()`	x
`rocsparse_Xcsr2dense()`	x
`rocsparse_Xcsc2dense()`	x
`rocsparse_Xcoo2dense()`	x
`rocsparse_Xnnz_compress()`	x
`rocsparse_Xnnz()`	x
`rocsparse_Xprune_dense2csr_buffer_size()`	x
`rocsparse_Xprune_dense2csr_nnz()`	x
`rocsparse_Xprune_dense2csr()`	x
`rocsparse_Xprune_csr2csr_buffer_size()`	x
`rocsparse_Xprune_csr2csr_nnz()`	x
`rocsparse_Xprune_csr2csr()`	x
`rocsparse_Xprune_dense2csr_by_percentage_buffer_size()`	x
`rocsparse_Xprune_dense2csr_nnz_by_percentage()`	x
`rocsparse_Xprune_dense2csr_by_percentage()`	x
`rocsparse_Xprune_csr2csr_by_percentage_buffer_size()`	x
`rocsparse_Xprune_csr2csr_nnz_by_percentage()`	x
`rocsparse_Xprune_csr2csr_by_percentage()`	x
`rocsparse_Xbsrpad_value()`	x

Reordering Functions#

Function name	yes	no
`rocsparse_Xcsrcolor()`	x

Utility Functions#

Function name	yes	no
`rocsparse_Xcheck_matrix_csr_buffer_size()`	x
`rocsparse_Xcheck_matrix_csr()`	x
`rocsparse_Xcheck_matrix_csc_buffer_size()`	x
`rocsparse_Xcheck_matrix_csc()`	x
`rocsparse_Xcheck_matrix_coo_buffer_size()`	x
`rocsparse_Xcheck_matrix_coo()`	x
`rocsparse_Xcheck_matrix_gebsr_buffer_size()`	x
`rocsparse_Xcheck_matrix_gebsr()`	x
`rocsparse_Xcheck_matrix_gebsc_buffer_size()`	x
`rocsparse_Xcheck_matrix_gebsc()`	x
`rocsparse_Xcheck_matrix_ell_buffer_size()`	x
`rocsparse_Xcheck_matrix_ell()`	x
`rocsparse_check_matrix_hyb_buffer_size()`	x
`rocsparse_check_matrix_hyb()`	x

Sparse Generic Functions#

Function name	yes	no
`rocsparse_axpby()`	x
`rocsparse_gather()`	x
`rocsparse_scatter()`	x
`rocsparse_rot()`	x
`rocsparse_spvv()`	x
`rocsparse_sparse_to_dense()`	x
`rocsparse_dense_to_sparse()`	x
`rocsparse_spsv()`		x
`rocsparse_spsm()`		x
`rocsparse_spgemm()`		x
`rocsparse_sddmm_buffer_size()`	x
`rocsparse_sddmm_preprocess()`	x
`rocsparse_sddmm()`	x
`rocsparse_sparse_to_sparse_buffer_size()`	x
`rocsparse_sparse_to_sparse()`	x
`rocsparse_extract_buffer_size()`	x
`rocsparse_extract()`	x

The reproducibility of rocsparse_spmv() is more complicated because this generic routine supports multiple sparse matrix formats and algorithms. See the below chart to determine whether a given algorithm is deterministic.

Bit-wise reproducibility of SpMV
Algorithm	A non-transpose		A transpose
Algorithm	Yes	No	Yes	No
rocsparse_spmv_alg_csr_stream	x			x
rocsparse_spmv_alg_csr_adaptive		x		x
rocsparse_spmv_alg_csr_lrb		x		x
rocsparse_spmv_alg_csr_stream (CSC FORMAT)		x	x
rocsparse_spmv_alg_csr_adaptive (CSC FORMAT)		x		x
rocsparse_spmv_alg_csr_lrb (CSC FORMAT)		x		x
rocsparse_spmv_alg_coo	x			x
rocsparse_spmv_alg_coo_atomic		x		x
rocsparse_spmv_alg_ell	x		N/A	N/A
rocsparse_spmv_alg_bsr	x		N/A	N/A

The reproducibility of rocsparse_spmm() is more complicated because this generic routine supports multiple sparse matrix formats and algorithms. See the below chart to determine whether a given algorithm is deterministic.

Bit-wise reproducibility of SpMM
Algorithm	A non-transpose		A transpose
Algorithm	Yes	No	Yes	No
rocsparse_spmm_alg_csr	x			x
rocsparse_spmm_alg_csr_row_split	x			x
rocsparse_spmm_alg_csr_nnz_split		x		x
rocsparse_spmm_alg_csr_merge_path		x		x
rocsparse_spmm_alg_csr (CSC FORMAT)		x	x
rocsparse_spmm_alg_csr_row_split (CSC FORMAT)		x	x
rocsparse_spmm_alg_csr_nnz_split (CSC FORMAT)		x		x
rocsparse_spmm_alg_csr_merge_path (CSC FORMAT)		x		x
rocsparse_spmm_alg_coo_segmented	x			x
rocsparse_spmm_alg_coo_atomic		x		x
rocsparse_spmm_alg_coo_segmented_atomic		x		x
rocsparse_spmm_alg_bell	x		N/A	N/A
rocsparse_spmm_alg_bsr	x		N/A	N/A