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TheRock/rocm-libraries/projects/rocblas/clients/gtest/spmv_gtest.yaml
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Flatten subprojects into a single base monorepo
2026-09-02 16:34:47 -07:00

321 lines
7.9 KiB
YAML

---
include: rocblas_common.yaml
include: known_bugs.yaml
Definitions:
- &special_case_range
- { N: 0, incx: 1, incy: 1, batch_count: 1 }
- { N: 1, incx: 1, incy: 1, batch_count: 0 }
- { N: -1, incx: 1, incy: 1, batch_count: 0 }
- { N: 0, incx: 0, incy: 1, batch_count: 0 }
- { N: 0, incx: 1, incy: 0, batch_count: 0 }
- { N: 0, incx: 1, incy: 1, batch_count: -1 }
- &medium_matrix_size_range
- { N: -1 }
- { N: 3 }
- { N: 10 }
- { N: 500 }
- &large_matrix_size_range
- { N: 4011 }
- { N: 8000 }
- &incx_incy_range
- { incx: 1, incy: 1 }
- { incx: 0, incy: -1 }
- { incx: 2, incy: 1 }
- { incx: -1, incy: -1 }
- &incx_incy_range_small
- { incx: 2, incy: -2 }
- &alpha_beta_range
- { alpha: 1.0, beta: 0.0 }
- { alpha: 0.0, beta: 1.0 }
- { alpha: -1.0, beta: -1.0 }
- { alpha: 2.0, beta: 1.0 }
- &alpha_beta_range_small
- { alpha: 2.0, beta: 1.5 }
- &alpha_beta_range_nan
- { alpha: .NaN, beta: 1.5 }
- { alpha: 1.5, beta: .NaN } # alpha value changed from 1.2 -> 1.5 to overcome the equality issue when comparing results of rocBLAS with the host
- &alpha_beta_range_size_t_inc
- { alpha: 0, alphai: 0, beta: 0.5, betai: 0 } # only incy used
- { alpha: 1, alphai: 0, beta: 0.5, betai: 0 }
- &size_t_index
- { N: 65536 } # overflow packed index as int (n*(n+1)/2)
- &size_t_incx_incy
- { N: 3, lda: 3, incx: *c_pos_x2_overflow_int32, incy: 1 }
- { N: 3, lda: 3, incx: 1, incy: *c_pos_x2_overflow_int32 }
Tests:
- name: spmv_bad
category: quick
function: spmv_bad_arg
precision: *single_precision
api: [ C, FORTRAN, FORTRAN_64 ]
- name: spmv_arg_check
category: quick
function:
- spmv
- spmv_batched
- spmv_strided_batched
precision: *single_double_precisions
uplo: L
matrix_size: *special_case_range
- name: spmv_fortran
category: quick
function: spmv
precision: *single_double_precisions
uplo: [ U, L ]
matrix_size: *medium_matrix_size_range
incx_incy: *incx_incy_range_small
alpha_beta: *alpha_beta_range_small
api: FORTRAN
- name: spmv_NaN
category: pre_checkin
function: spmv
precision: *single_double_precisions
uplo: [ U ]
N: [ 33 ]
incx_incy: *incx_incy_range_small
alpha_beta: *alpha_beta_range_nan
- name: spmv_medium
category: pre_checkin
function: spmv
precision: *single_double_precisions
uplo: [ U, L ]
matrix_size: *medium_matrix_size_range
incx_incy: *incx_incy_range
alpha_beta: *alpha_beta_range
- name: spmv_large
category: nightly
function: spmv
precision: *single_double_precisions
uplo: [ U, L ]
matrix_size: *large_matrix_size_range
incx_incy: *incx_incy_range_small
alpha_beta: *alpha_beta_range_small
- name: spmv_size_t
category: stress
function: spmv
precision: *single_precision
uplo: [ U, L ]
matrix_size: *size_t_index
incx: 1
incy: 1
alpha_beta: *alpha_beta_range_small
pointer_mode_host: false
os_flags: LINUX
gpu_arch: ['90a','942','950']
- name: spmv_size_t_inc
category: stress
function: spmv
precision: *single_precision
uplo: [ U, L ]
arguments: *size_t_incx_incy
alpha_beta: *alpha_beta_range_size_t_inc
pointer_mode_device: false
os_flags: LINUX
gpu_arch: ['90a','942','950']
- name: spmv_ILP64
category: stress
arguments:
- { N: 2, incx: 2147483649, incy: 1, batch_count: 1 }
- { N: 2, incx: 1, incy: -2147483649, batch_count: 1 }
- { N: 2, stride_a: 4, incx: 1, incy: 1, batch_count: *c_grid_yz_require_passes }
uplo: [ U, L ]
stride_scale: [ 1 ]
alpha_beta: *alpha_beta_range_small
pointer_mode_host: false
api: [ C_64 ]
os_flags: [ LINUX ]
function:
- spmv: *single_precision
- spmv_batched: *single_precision
- spmv_strided_batched: *single_precision
# batched
- name: spmv_batched_bad
category: quick
function: spmv_batched_bad_arg
precision: *single_precision
api: [ C, FORTRAN ]
- name: spmv_batched_fortran
category: quick
function: spmv_batched
precision: *single_double_precisions
uplo: [ U, L ]
matrix_size: *medium_matrix_size_range
incx_incy: *incx_incy_range_small
alpha_beta: *alpha_beta_range_small
batch_count: [ -1, 0, 3 ]
api: FORTRAN
- name: spmv_batched_NaN
category: pre_checkin
function: spmv_batched
precision: *double_precision
uplo: [ U ]
N: [ 33 ]
incx_incy: *incx_incy_range_small
alpha_beta: *alpha_beta_range_nan
batch_count: [ 2 ]
- name: spmv_batched_medium
category: pre_checkin
function: spmv_batched
precision: *single_double_precisions
uplo: [ U, L ]
matrix_size: *medium_matrix_size_range
incx_incy: *incx_incy_range
alpha_beta: *alpha_beta_range
batch_count: [ -1, 0, 1, 257 ]
pointer_mode_host: false
- name: spmv_batched_large
category: nightly
function: spmv_batched
precision: *single_double_precisions
uplo: [ U, L ]
matrix_size: *large_matrix_size_range
incx_incy: *incx_incy_range_small
alpha_beta: *alpha_beta_range_small
batch_count: [ 1, 3 ]
pointer_mode_device: false
- name: spmv_batched_grid_z_16bit
category: stress
arguments:
- { N: 3, lda: 3, incx: 1, incy: 1, batch_count: *c_grid_yz_require_passes} #generic kernel
uplo: [ U, L ]
alpha_beta: *alpha_beta_range_small
pointer_mode_host: false
function:
- spmv_batched: *single_precision
- spmv_strided_batched: *single_precision
stride_scale: 1
# strided batched
- name: spmv_strided_batched_bad
category: quick
function: spmv_strided_batched_bad_arg
precision: *single_precision
api: [ C, FORTRAN ]
- name: spmv_strided_batched_fortran
category: quick
function: spmv_strided_batched
precision: *single_double_precisions
uplo: [ U, L ]
matrix_size: *medium_matrix_size_range
incx_incy: *incx_incy_range_small
alpha_beta: *alpha_beta_range_small
batch_count: [ -1, 0, 3 ]
api: FORTRAN
- name: spmv_strided_batched_NaN
category: pre_checkin
function: spmv_strided_batched
precision: *single_double_precisions
uplo: [ L ]
N: [ 33 ]
incx_incy: *incx_incy_range_small
alpha_beta: *alpha_beta_range_nan
batch_count: [ 2 ]
- name: spmv_strided_batched_medium
category: pre_checkin
function: spmv_strided_batched
precision: *single_double_precisions
uplo: [ U, L ]
matrix_size: *medium_matrix_size_range
incx_incy: *incx_incy_range
alpha_beta: *alpha_beta_range
batch_count: [ -1, 0, 1, 257 ]
pointer_mode_device: false
- name: spmv_strided_batched_large
category: nightly
function: spmv_strided_batched
precision: *single_double_precisions
uplo: [ U, L ]
matrix_size: *large_matrix_size_range
incx_incy: *incx_incy_range_small
alpha_beta: *alpha_beta_range_small
batch_count: [ 1, 3 ]
pointer_mode_host: false
- name: spmv_graph_test
category: pre_checkin
function:
- spmv
- spmv_batched
- spmv_strided_batched
precision: *single_double_precisions
matrix_size:
- { N : 33 }
uplo: [ U ]
incx: [ 1 ]
alpha: [ 2.0 ]
stride_scale: [ 1 ]
batch_count: [ 5 ]
graph_test: true
- name: spmv_repeatability_check
category: stress
function:
- spmv
- spmv_batched
- spmv_strided_batched
precision: *single_double_precisions
matrix_size:
- { N : 33 }
uplo: [ U ]
incx: [ 1 ]
alpha: [ 2.0 ]
stride_scale: [ 1 ]
batch_count: [ 2 ]
initialization: hpl
atomics_mode: 0
pointer_mode_host: false
iters: 5
devices: 4
repeatability_check: true
# per-batch alpha/beta (rocblas_set_batch_alpha_stride / rocblas_set_batch_beta_stride)
# coverage, device pointer mode only
- name: spmv_stride_alpha_beta
category: pre_checkin
function:
- spmv_batched
- spmv_strided_batched
precision: *single_double_precisions
uplo: [ U, L ]
matrix_size: *medium_matrix_size_range
incx_incy: *incx_incy_range
alpha_beta: *alpha_beta_range_small
stride_scale: [ 1 ]
batch_count: [ 3 ]
alpha_beta_stride: true
stride_c: 2 # alpha stride
stride_d: 2 # beta stride
pointer_mode_host: false
...