--- include: rocblas_common.yaml include: known_bugs.yaml Definitions: - &quick_matrix_size_range - { N: -1, lda: 1, K: 1, ldc: 1 } # bad n - { N: 2, lda: 2, K: -1, ldc: 1 } # bad k - { N: 0, lda: 3, K: 3, ldc: 3 } # n==0 - { N: 3, lda: 3, K: 0, ldc: 3 } # k==0 - { N: 3, lda: 1, K: 1, ldc: 3 } # bad lda if not transpose - { N: 1, lda: 1, K: 3, ldc: 3 } # bad lda if transpose - { N: 3, lda: 3, K: 3, ldc: 1 } # bad ldc - &tiny_matrix_size - { N: 199, lda: 199, K: 32, ldc: 199 } #test the kernels which uses only gemm to compute syrk - { N: 2, lda: 501, K: 501, ldc: 2 } - &medium_matrix_size_range - { N: 199, lda: 199, K: 32, ldc: 199 } - { N: 88, lda: 200, K: 200, ldc: 88 } #test the kernels which uses only gemm to compute syrk - { N: 51, lda: 201, K: 201, ldc: 51 } - { N: 601, lda: 806, K: 805, ldc: 601 } - &large_matrix_size_range - { N: 2011, lda: 2011, K: 253, ldc: 2048 } - { N: 2048, lda: 2048, K: 512, ldc: 2048 } - { N: 5000, lda: 5008, K: 164, ldc: 5000 } #test the kernels which uses only gemm to compute syrk - { N: 601, lda: 2001, K: 2001, ldc: 601 } - { N: 64, lda: 5000, K: 5000, ldc: 64 } - &matrix_size_kernel_scan - { N: 512, lda: 512, K: 512, ldc: 512 } - &alpha_beta_kernel_scan - { alpha: 1.0, alphai: 0.0, beta: 1.0, betai: 0.0 } - { alpha: 1.0, alphai: 0.0, beta: -1.0, betai: 0.0 } - { alpha: 1.0, alphai: 0.0, beta: 0.0, betai: 0.0 } - { alpha: -1.0, alphai: 0.0, beta: 0.0, betai: 0.0 } - { alpha: 2.0, alphai: 0.0, beta: 0.0, betai: 0.0 } - { alpha: 0.5, alphai: 0.0, beta: 0.5, betai: 0.0 } - &alpha_beta_range - { alpha: 1.0, alphai: 0.0, beta: 1.0, betai: 0.0 } - { alpha: -2.0, alphai: 1.0, beta: -1.0, betai: 0.5 } - { alpha: 0.0, alphai: 0.0, beta: 1.0, betai: 0.0 } # quick success - { alpha: 0.0, alphai: 0.0, beta: 2.0, betai: 0.5 } # scale step only - &alpha_beta - { alpha: -1.0, alphai: 0.5, beta: -0.5, betai: 0.5 } # These larger values below on large_matrices require a tolerance rather than equality # due to least significant digit difference CPU to GPU on windows # I expect only accumulation difference from scheduling variation on windows # - { alpha: -2.1, alphai: 1.3, beta: -0.5, betai: 0.6 } Tests: # # herk_ex # - name: herk_ex_bad category: quick function: - herk_ex_bad_arg # - herk_ex_batched_bad_arg # - herk_ex_strided_batched_bad_arg precision: *herk_ex_precisions api: [ C, FORTRAN ] - name: herk_ex_quick category: quick function: herk_ex precision: *herk_ex_precisions uplo: [ U, L ] transA: [ N, C ] matrix_size: *quick_matrix_size_range alpha_beta: *alpha_beta_range initialization: rand_int - name: herk_ex_NaN category: pre_checkin function: herk_ex precision: *herk_ex_precisions uplo: [ U ] transA: [ N ] matrix_size: *tiny_matrix_size alpha: [ 2.0, .NaN ] # NaN is converted to 0.0 in test code beta: [ 1.0, .NaN ] - name: herk_ex_pre_checkin category: pre_checkin function: herk_ex precision: *herk_ex_precisions uplo: [ U, L ] transA: [ N, C ] matrix_size: *medium_matrix_size_range alpha_beta: *alpha_beta_range devices: 1 initialization: rand_int - name: herk_ex_kernel_scan category: pre_checkin function: herk_ex precision: *herk_ex_precisions uplo: [ U, L ] transA: [ N, C ] matrix_size: *matrix_size_kernel_scan alpha_beta: *alpha_beta_kernel_scan initialization: hpl - name: herk_ex_nighlty category: nightly function: herk_ex precision: *herk_ex_precisions uplo: [ U, L ] transA: [ N, C ] matrix_size: *large_matrix_size_range alpha_beta: *alpha_beta_range initialization: hpl - name: herk_ex_graph_test category: pre_checkin function: - herk_ex precision: *herk_ex_precisions uplo: [ L ] transA: [ N, C ] matrix_size: - { N: 199, K: 33, lda: 199, ldc: 199 } - { N: 32, K: 32, lda: 32, ldc: 32 } alpha: [ 1 ] beta: [ 1 ] graph_test: true - name: herk_ex_repeatability_check category: pre_checkin function: herk_ex precision: *herk_ex_precisions uplo: [ U, L ] transA: [ N, C ] matrix_size: *medium_matrix_size_range alpha: [ 1 ] beta: [ 1 ] devices: 1 repeatability_check: true initialization: hpl ...