.. SPDX-FileCopyrightText: 2022 Intel Corporation .. .. SPDX-License-Identifier: CC-BY-4.0 .. _onemkl_blas_omatadd_batch: omatadd_batch ============= Computes a group of out-of-place scaled matrix additions using general dense matrices. .. _onemkl_blas_omatadd_batch_description: .. rubric:: Description The ``omatadd_batch`` routines perform a series of out-of-place scaled matrix additions. They are batched versions of :ref:`onemkl_blas_omatadd`, but the ``omatadd_batch`` routines perform their operations with groups of matrices. Each group contains matrices with the same parameters. There is a *strided API*, in which the matrices in a batch are a set distance away from each other in memory and in which all matrices share the same parameters (for example matrix size), and a more flexible *group API* where each group of matrices has the same parameters but the user may provide multiple groups that have different parameters. The group API argument structure is better suited to USM pointers than to ``sycl::buffer`` arguments, so we only specify it for USM inputs. The strided API works with both USM and buffer memory. .. list-table:: :header-rows: 1 * - - strided API - group API * - Buffer memory - supported - not supported * - USM pointers - supported - supported ``omatadd_batch`` supports the following precisions: .. list-table:: :header-rows: 1 * - T * - ``float`` * - ``double`` * - ``std::complex`` * - ``std::complex`` .. _onemkl_blas_omatadd_batch_buffer: omatadd_batch (Buffer Version) ------------------------------ .. rubric:: Description The buffer version of ``omatcopy_batch`` supports only the strided API. The operation of ``omatadd_batch`` is defined as: :: for i = 0 … batch_size – 1 A is a matrix at offset i * stridea in a B is a matrix at offset i * strideb in b C is a matrix at offset i * stridec in c C := alpha * op(A) + beta * op(B) end for where: op(X) is one of op(X) = X, or op(X) = X\ :sup:`T`, or op(X) = X\ :sup:`H`, ``alpha`` and ``beta`` are scalars, ``A`` and ``B`` are input matrices while ``C`` is an output matrix, ``C`` is ``m`` x ``n``, ``A`` is ``m`` x ``n`` if the ``op(A)`` is not transposed or ``n`` by ``m`` if it is, and ``B`` is ``m`` x ``n`` if the ``op(B)`` is not transposed or ``n`` by ``m`` if it is. The ``a`` and ``b`` buffers contain all the input matrices while the ``c`` buffer contains all the output matrices. The locations of the individual matrices within the buffer are given by the ``stride_a``, ``stride_b``, and ``stride_c`` parameters, while the total number of matrices in each buffer is given by the ``batch_size`` parameter. In general, the ``a``, ``b``, and ``c`` buffers should not overlap in memory, with the exception of the following in-place operations: - ``a`` and ``c`` may point to the same memory if ``op(A)`` is non-transpose and all the ``A`` matrices have the same parameters as all the respective ``C`` matrices; - ``b`` and ``c`` may point to the same memory if ``op(B)`` is non-transpose and all the ``B`` matrices have the same parameters as all the respective ``C`` matrices. **Strided API** .. rubric:: Syntax .. code-block:: cpp namespace oneapi::mkl::blas::column_major { void omatadd_batch(sycl::queue &queue, oneapi::mkl::transpose transa, oneapi::mkl::transpose transb, std::int64_t m, std::int64_t n, T alpha, sycl::buffer &a, std::int64_t lda, std::int64_t stride_a, T beta, sycl::buffer &b, std::int64_t ldb, std::int64_t stride_b, sycl::buffer &c, std::int64_t ldc, std::int64_t stride_c, std::int64_t batch_size); } .. code-block:: cpp namespace oneapi::mkl::blas::row_major { void omatadd_batch(sycl::queue &queue, oneapi::mkl::transpose transa, oneapi::mkl::transpose transb, std::int64_t m, std::int64_t n, T alpha, sycl::buffer &a, std::int64_t lda, std::int64_t stride_a, T beta, sycl::buffer &b, std::int64_t ldb, std::int64_t stride_b, sycl::buffer &c, std::int64_t ldc, std::int64_t stride_c, std::int64_t batch_size); } .. container:: section .. rubric:: Input Parameters queue The queue where the routine should be executed. transa Specifies op(``A``), the transposition operation applied to the matrices ``A``. See :ref:`onemkl_datatypes` for more details. transb Specifies op(``B``), the transposition operation applied to the matrices ``B``. See :ref:`onemkl_datatypes` for more details. m Number of rows for the result matrix ``C``. Must be at least zero. n Number of columns for the result matrix ``C``. Must be at least zero. alpha Scaling factor for the matrices ``A``. a Buffer holding the input matrices ``A``. Must have size at least ``stride_a`` * ``batch_size``. lda The leading dimension of the matrices ``A``. It must be positive. .. list-table:: :header-rows: 1 * - - ``A`` not transposed - ``A`` transposed * - Column major - ``lda`` must be at least ``m``. - ``lda`` must be at least ``n``. * - Row major - ``lda`` must be at least ``n``. - ``lda`` must be at least ``m``. stride_a Stride between the different ``A`` matrices within the buffer. .. list-table:: :header-rows: 1 * - - ``A`` not transposed - ``A`` transposed * - Column major - ``stride_a`` must be at least ``lda*n``. - ``stride_a`` must be at least ``lda*m``. * - Row major - ``stride_a`` must be at least ``lda*m``. - ``stride_a`` must be at least ``lda*n``. beta Scaling factor for the matrices ``B``. b Buffer holding the input matrices ``B``. Must have size at least ``stride_b`` * ``batch_size``. ldb The leading dimension of the ``B`` matrices. It must be positive. .. list-table:: :header-rows: 1 * - - ``B`` not transposed - ``B`` transposed * - Column major - ``ldb`` must be at least ``m``. - ``ldb`` must be at least ``n``. * - Row major - ``ldb`` must be at least ``n``. - ``ldb`` must be at least ``m``. stride_b Stride between different ``B`` matrices. .. list-table:: :header-rows: 1 * - - ``B`` not transposed - ``B`` transposed * - Column major - ``stride_b`` must be at least ``ldb`` x ``n``. - ``stride_b`` must be at least ``ldb`` x ``m``. * - Row major - ``stride_b`` must be at least ``ldb`` x ``m``. - ``stride_b`` must be at least ``ldb`` x ``n``. c Buffer holding the output matrices ``C``. Must have size at least ``stride_c`` * ``batch_size``. ldc Leading dimension of the ``C`` matrices. If matrices are stored using column major layout, ``ldc`` must be at least ``m``. If matrices are stored using row major layout, ``ldc`` must be at least ``n``. Must be positive. stride_c Stride between the different ``C`` matrices. If matrices are stored using column major layout, ``stride_c`` must be at least ``ldc*n``. If matrices are stored using row major layout, ``stride_c`` must be at least ``ldc*m``. batch_size Specifies the number of matrix transposition or copy operations to perform. .. container:: section .. rubric:: Output Parameters c Output buffer, overwritten by ``batch_size`` matrix addition operations of the form ``alpha*op(A) + beta*op(B)``. Must have size at least ``stride_c*batch_size``. .. container:: section .. rubric:: Throws This routine shall throw the following exceptions if the associated condition is detected. An implementation may throw additional implementation-specific exception(s) in case of error conditions not covered here. :ref:`oneapi::mkl::invalid_argument` :ref:`oneapi::mkl::unsupported_device` :ref:`oneapi::mkl::host_bad_alloc` :ref:`oneapi::mkl::device_bad_alloc` :ref:`oneapi::mkl::unimplemented` .. _onemkl_blas_omatadd_batch_usm: omatadd_batch (USM Version) --------------------------- .. rubric:: Description The USM version of ``omatadd_batch`` supports the group API and the strided API. The operation for the group API is defined as: :: idx = 0 for i = 0 … group_count – 1 m, n, alpha, beta, lda, ldb, ldc and group_size at position i in their respective arrays for j = 0 … group_size – 1 A, B and C are matrices at position idx in their respective arrays C := alpha * op(A) + beta * op(B) idx := idx + 1 end for end for The operation for the strided API is defined as: :: for i = 0 … batch_size – 1 A is a matrix at offset i * stridea in a B is a matrix at offset i * strideb in b C is a matrix at offset i * stridec in c C := alpha * op(A) + beta * op(B) end for where: op(X) is one of op(X) = X, or op(X) = X\ :sup:`T`, or op(X) = X\ :sup:`H`, ``alpha`` and ``beta`` are scalars, ``A`` and ``B`` are input matrices while ``C`` is an output matrix, ``C`` is ``m`` x ``n``, ``A`` is ``m`` x ``n`` if the ``op(A)`` is not transposed or ``n`` by ``m`` if it is, and ``B`` is ``m`` x ``n`` if the ``op(B)`` is not transposed or ``n`` by ``m`` if it is. For the group API, the matrices are given by arrays of pointers. ``A``, ``B``, and ``C`` represent matrices stored at addresses pointed to by ``a_array``, ``b_array``, and ``c_array`` respectively. The number of entries in ``a_array``, ``b_array``, and ``c_array`` is given by: .. math:: total\_batch\_count = \sum_{i=0}^{group\_count-1}group\_size[i] For the strided API, the ``a`` and ``b`` arrays contain all the input matrices while the ``c`` array contains all the output matrices. The locations of the individual matrices within the array are given by the ``stride_a``, ``stride_b``, and ``stride_c`` parameters, while the total number of matrices in each array is given by the ``batch_size`` parameter. In general, the batches of matrices indicated by ``a``, ``b``, and ``c`` should not overlap in memory, with the exception of the the following in-place operations: - ``a`` and ``c`` may point to the same memory if ``op(A)`` is non-transpose and all the ``A`` matrices have identical parameters as all the respective ``C`` matrices; - ``b`` and ``c`` may point to the same memory if ``op(B)`` is non-transpose and all the the ``B`` matrices have identical parameters as all the respective ``C`` matrices. **Group API** .. rubric:: Syntax .. code-block:: cpp namespace oneapi::mkl::blas::column_major { sycl::event omatadd_batch(sycl::queue &queue, const oneapi::mkl::transpose *transa_array, const oneapi::mkl::transpose *transb_array, const std::int64_t *m_array, const std::int64_t *n_array, const T *alpha_array, const T **a_array, const std::int64_t *lda_array, const T *beta_array, const T **b_array, const std::int64_t *ldb_array, const T **c_array, const std::int64_t *ldc_array, std::int64_t group_count, const std::int64_t *groupsize, const std::vector &dependencies = {}); } .. code-block:: cpp namespace oneapi::mkl::blas::row_major { sycl::event omatadd_batch(sycl::queue &queue, const oneapi::mkl::transpose *transa_array, const oneapi::mkl::transpose *transb_array, const std::int64_t *m_array, const std::int64_t *n_array, const T *alpha_array, const T **a_array, const std::int64_t *lda_array, const T *beta_array, const T **b_array, const std::int64_t *ldb_array, const T **c_array, const std::int64_t *ldc_array, std::int64_t group_count, const std::int64_t *groupsize, const std::vector &dependencies = {}); } .. container:: section .. rubric:: Input Parameters queue The queue where the routine should be executed. transa_array Array of size ``group_count``. Each element ``i`` in the array specifies ``op(A)`` the transposition operation applied to the matrices A. transb_array Array of size ``group_count``. Each element ``i`` in the array specifies ``op(B)`` the transposition operation applied to the matrices B. m_array Array of size ``group_count`` of number of rows of ``C``. Each must be at least 0. n_array Array of size ``group_count`` of number of columns of ``C``. Each must be at least 0. alpha_array Array of size ``group_count`` containing scaling factors for the matrices ``A``. a_array Array of size ``total_batch_count``, holding pointers to arrays used to store ``A`` matrices. The array allocated for each ``A`` matrix of the group ``i`` must be of size at least: .. list-table:: :header-rows: 1 * - - ``transa[i]`` = ``transpose::nontrans`` - ``transa[i]`` = ``transpose::trans`` or ``transa[i]`` = ``transpose::conjtrans`` * - Column major - ``lda_array[i]`` * ``n_array[i]`` - ``lda_array[i]`` * ``m_array[i]`` * - Row major - ``lda_array[i]`` * ``m_array[i]`` - ``lda_array[i]`` * ``n_array[i]`` lda_array Array of size ``group_count`` of leading dimension of the A matrices. All must be positive and satisfy: .. list-table:: :header-rows: 1 * - - ``transa[i]`` = ``transpose::nontrans`` - ``transa[i]`` = ``transpose::trans`` or ``transa`` = ``transpose::conjtrans`` * - Column major - ``lda_array[i]`` must be at least ``m_array[i]``. - ``lda_array[i]`` must be at least ``n_array[i]``. * - Row major - ``lda_array[i]`` must be at least ``n_array[i]``. - ``lda_array[i]`` must be at least ``m_array[i]``. beta_array Array of size ``group_count`` containing scaling factors for the matrices ``B``. b_array Array of size ``total_batch_count`` of pointers used to store the B matrices. The array allocated for each B matrix of the group ``i`` must be of size at least: .. list-table:: :header-rows: 1 * - - ``transb[i]`` = ``transpose::nontrans`` - ``transb[i]`` = ``transpose::trans`` or ``transb[i]`` = ``transpose::conjtrans`` * - Column major - ``ldb_array[i]`` * ``n_array[i]`` - ``ldb_array[i]`` * ``m_array[i]`` * - Row major - ``ldb_array[i]`` * ``m_array[i]`` - ``ldb_array[i]`` * ``n_array[i]`` ldb_array Array of size ``group_count``. The leading dimension of ``B`` matrices. All must be positive and satisfy: .. list-table:: :header-rows: 1 * - - ``transb[i]`` = ``transpose::nontrans`` - ``transb[i]`` = ``transpose::trans`` or ``transb[i]`` = ``transpose::conjtrans`` * - Column major - ``ldb_array[i]`` must be at least ``m_array[i]``. - ``ldb_array[i]`` must be at least ``n_array[i]``. * - Row major - ``ldb_array[i]`` must be at least ``n_array[i]``. - ``ldb_array[i]`` must be at least ``m_array[i]``. c_array Array of size ``total_batch_count`` of pointers used to store the ``C`` output matrices. The array allocated for each C matrix of the group ``i`` must be of size at least: .. list-table:: * - Column major - ``ldc_array[i]`` * ``n_array[i]`` * - Row major - ``ldc_array[i]`` * ``m_array[i]`` ldc_array Array of size ``group_count``. The leading dimension of the ``C`` matrices. If matrices are stored using column major layout, ``ldc_array[i]`` must be at least ``m_array[i]``. If matrices are stored using row major layout, ``ldc_array[i]`` must be at least ``n_array[i]``. All entries must be positive. group_count Number of groups. Must be at least 0. group_size Array of size ``group_count``. The element ``group_size[i]`` is the number of matrices in the group ``i``. Each element in ``group_size`` must be at least 0. dependencies List of events to wait for before starting computation, if any. If omitted, defaults to no dependencies. .. container:: section .. rubric:: Output Parameters c_array Output array of pointers to C matrices, overwritten by ``total_batch_count`` matrix addition operations of the form ``alpha*op(A) + beta*op(B)``. .. container:: section .. rubric:: Return Values Output event to wait on to ensure computation is complete. **Strided API** .. rubric:: Syntax .. code-block:: cpp namespace oneapi::mkl::blas::column_major { sycl::event omatadd_batch(sycl::queue &queue, oneapi::mkl::transpose transa, oneapi::mkl::transpose transb, std::int64_t m, std::int64_t n, T alpha, const T *a, std::int64_t lda, std::int64_t stride_a, T beta, T *b, std::int64_t ldb, std::int64_t stride_b, T *c, std::int64_t ldc, std::int64_t stride_c, std::int64_t batch_size, const std::vector &dependencies = {}); } .. code-block:: cpp namespace oneapi::mkl::blas::row_major { sycl::event omatadd_batch(sycl::queue &queue, oneapi::mkl::transpose transa, oneapi::mkl::transpose transb, std::int64_t m, std::int64_t n, T alpha, const T *a, std::int64_t lda, std::int64_t stride_a, T beta, T *b, std::int64_t ldb, std::int64_t stride_b, T *c, std::int64_t ldc, std::int64_t stride_c, std::int64_t batch_size, const std::vector &dependencies = {}); } .. container:: section .. rubric:: Input Parameters queue The queue where the routine should be executed. transa Specifies op(``A``), the transposition operation applied to the matrices ``A``. See :ref:`onemkl_datatypes` for more details. transb Specifies op(``B``), the transposition operation applied to the matrices ``B``. See :ref:`onemkl_datatypes` for more details. m Number of rows for the result matrix ``C``. Must be at least zero. n Number of columns for the result matrix ``C``. Must be at least zero. alpha Scaling factor for the matrices ``A``. a Array holding the input matrices ``A``. Must have size at least ``stride_a`` * ``batch_size``. lda The leading dimension of the matrices ``A``. It must be positive. .. list-table:: :header-rows: 1 * - - ``A`` not transposed - ``A`` transposed * - Column major - ``lda`` must be at least ``m``. - ``lda`` must be at least ``n``. * - Row major - ``lda`` must be at least ``n``. - ``lda`` must be at least ``m``. stride_a Stride between the different ``A`` matrices within the array. .. list-table:: :header-rows: 1 * - - ``A`` not transposed - ``A`` transposed * - Column major - ``stride_a`` must be at least ``lda*n``. - ``stride_a`` must be at least ``lda*m``. * - Row major - ``stride_a`` must be at least ``lda*m``. - ``stride_a`` must be at least ``lda*n``. beta Scaling factor for the matrices ``B``. b Array holding the input matrices ``B``. Must have size at least ``stride_b`` * ``batch_size``. ldb The leading dimension of the ``B`` matrices. It must be positive. .. list-table:: :header-rows: 1 * - - ``B`` not transposed - ``B`` transposed * - Column major - ``ldb`` must be at least ``m``. - ``ldb`` must be at least ``n``. * - Row major - ``ldb`` must be at least ``n``. - ``ldb`` must be at least ``m``. stride_b Stride between different ``B`` matrices. .. list-table:: :header-rows: 1 * - - ``B`` not transposed - ``B`` transposed * - Column major - ``stride_b`` must be at least ``ldb`` x ``n``. - ``stride_b`` must be at least ``ldb`` x ``m``. * - Row major - ``stride_b`` must be at least ``ldb`` x ``m``. - ``stride_b`` must be at least ``ldb`` x ``n``. c Array holding the output matrices ``C``. Must have size at least ``stride_c`` * ``batch_size``. ldc Leading dimension of the ``C`` matrices. If matrices are stored using column major layout, ``ldc`` must be at least ``m``. If matrices are stored using row major layout, ``ldc`` must be at least ``n``. Must be positive. stride_c Stride between the different ``C`` matrices. If matrices are stored using column major layout, ``stride_c`` must be at least ``ldc*n``. If matrices are stored using row major layout, ``stride_c`` must be at least ``ldc*m``. batch_size Specifies the number of matrix transposition or copy operations to perform. dependencies List of events to wait for before starting computation, if any. If omitted, defaults to no dependencies. .. container:: section .. rubric:: Output Parameters c Output array, overwritten by ``batch_size`` matrix addition operations of the form ``alpha*op(A) + beta*op(B)``. Must have size at least ``stride_c*batch_size``. .. container:: section .. rubric:: Return Values Output event to wait on to ensure computation is complete. .. container:: section .. rubric:: Throws This routine shall throw the following exceptions if the associated condition is detected. An implementation may throw additional implementation-specific exception(s) in case of error conditions not covered here. :ref:`oneapi::mkl::invalid_argument` :ref:`oneapi::mkl::unsupported_device` :ref:`oneapi::mkl::host_bad_alloc` :ref:`oneapi::mkl::device_bad_alloc` :ref:`oneapi::mkl::unimplemented` **Parent topic:** :ref:`blas-like-extensions`