.. SPDX-FileCopyrightText: 2022 Intel Corporation .. .. SPDX-License-Identifier: CC-BY-4.0 .. _onemkl_blas_imatcopy_batch: imatcopy_batch ============== Computes a group of in-place scaled matrix transpose or copy operations using general dense matrices. .. _onemkl_blas_imatcopy_batch_description: .. rubric:: Description The ``imatcopy_batch`` routines perform a series of in-place scaled matrix copies or transpositions. They are batched versions of :ref:`onemkl_blas_imatcopy`, but the ``imatcopy_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 ``imatcopy_batch`` supports the following precisions: .. list-table:: :header-rows: 1 * - T * - ``float`` * - ``double`` * - ``std::complex`` * - ``std::complex`` .. _onemkl_blas_imatcopy_batch_buffer: imatcopy_batch (Buffer Version) ------------------------------- .. rubric:: Description The buffer version of ``imatcopy_batch`` supports only the strided API. The operation for the strided API is defined as: :: for i = 0 … batch_size – 1 C is a matrix at offset i * stride in matrix_array_in_out C := alpha * op(C) end for where: op(X) is one of op(X) = X, or op(X) = X\ :sup:`T`, or op(X) = X\ :sup:`H`, ``alpha`` is a scalar, ``C`` is a matrix to be transformed in place, and ``C`` is ``m`` x ``n``. The ``matrix_array_in_out`` buffer contains all the input matrices. The stride between matrices is given by the ``stride`` parameter. The total number of matrices in ``matrix_array_in_out`` is given by the ``batch_size`` parameter. **Strided API** .. rubric:: Syntax .. code-block:: cpp namespace oneapi::mkl::blas::column_major { void imatcopy_batch(sycl::queue &queue, oneapi::mkl::transpose trans, std::int64_t m, std::int64_t n, T alpha, sycl::buffer &matrix_array_in_out, std::int64_t ld_in, std::int64_t ld_out, std::int64_t stride, std::int64_t batch_size); } .. code-block:: cpp namespace oneapi::mkl::blas::row_major { void imatcopy_batch(sycl::queue &queue, oneapi::mkl::transpose trans, std::int64_t m, std::int64_t n, T alpha, sycl::buffer &matrix_array_in_out, std::int64_t ld_in, std::int64_t ld_out, std::int64_t stride, std::int64_t batch_size); } .. container:: section .. rubric:: Input Parameters queue The queue where the routine should be executed. trans Specifies op(``C``), the transposition operation applied to the matrices ``C``. See :ref:`onemkl_datatypes` for more details. m Number of rows of each matrix ``C`` on input. Must be at least zero. n Number of columns of each matrix ``C`` on input. Must be at least zero. alpha Scaling factor for the matrix transpositions or copies. matrix_array_in_out Buffer holding the input matrices ``C`` with size ``stride`` * ``batch_size``. ld_in The leading dimension of the matrices ``C`` on input. It must be positive, and must be at least ``m`` if column major layout is used, and at least ``n`` if row-major layout is used. ld_out The leading dimension of the matrices ``C`` on output. It must be positive. .. list-table:: :header-rows: 1 * - - ``C`` not transposed - ``C`` transposed * - Column major - ``ld_out`` must be at least ``m``. - ``ld_out`` must be at least ``n``. * - Row major - ``ld_out`` must be at least ``n``. - ``ld_out`` must be at least ``m``. stride Stride between different ``C`` matrices. .. list-table:: :header-rows: 1 * - - ``C`` not transposed - ``C`` transposed * - Column major - ``stride`` must be at least ``max(ld_in*m, ld_out*m)``. - ``stride`` must be at least ``max(ld_in*m, ld_out*n)``. * - Row major - ``stride`` must be at least ``max(ld_in*n, ld_out*n)``. - ``stride`` must be at least ``max(ld_in*n, ld_out*m)``. batch_size Specifies the number of matrix transposition or copy operations to perform. .. container:: section .. rubric:: Output Parameters matrix_array_in_out Output buffer, overwritten by ``batch_size`` matrix copy or transposition operations of the form ``alpha`` * op(``C``). .. 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_imatcopy_batch_usm: imatcopy_batch (USM Version) ---------------------------- .. rubric:: Description The USM version of ``imatcopy_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, ld_in, ld_out and group_size at position i in their respective arrays for j = 0 … group_size – 1 C is a matrix at position idx in matrix_array_in_out C := alpha * op(C) idx := idx + 1 end for end for The operation for the strided API is defined as: :: for i = 0 … batch_size – 1 C is a matrix at offset i * stride in matrix_array_in_out C := alpha * op(C) end for where: op(X) is one of op(X) = X, or op(X) = X\ :sup:`T`, or op(X) = X\ :sup:`H`, ``alpha`` is a scalar, ``C`` is a matrix to be transformed in place, and ``C`` is ``m`` x ``n``. For the group API, the matrices are given by arrays of pointers. ``C`` represents a matrix stored at the address pointed to by ``matrix_array_in_out``. The number of entries in ``matrix_array_in_out`` is given by: .. math:: total\_batch\_count = \sum_{i=0}^{group\_count-1}group\_size[i] For the strided API, the single array C contains all the matrices to be transformed in place. The locations of the individual matrices within the buffer or array are given by stride lengths, while the number of matrices is given by the ``batch_size`` parameter. **Group API** .. rubric:: Syntax .. code-block:: cpp namespace oneapi::mkl::blas::column_major { event imatcopy_batch(sycl::queue &queue, const oneapi::mkl::transpose *trans_array, const std::int64_t *m_array, const std::int64_t *n_array, const T *alpha_array, T **matrix_array_in_out, const std::int64_t *ld_in_array, const std::int64_t *ld_out_array, std::int64_t group_count, const std::int64_t *groupsize, const std::vector &dependencies = {}); } .. code-block:: cpp namespace oneapi::mkl::blas::row_major { event imatcopy_batch(sycl::queue &queue, const oneapi::mkl::transpose *trans_array, const std::int64_t *m_array, const std::int64_t *n_array, const T *alpha_array, T **matrix_array_in_out, const std::int64_t *ld_in_array, const std::int64_t *ld_out_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. trans_array Array of size ``group_count``. Each element ``i`` in the array specifies ``op(C)`` the transposition operation applied to the matrices C. m_array Array of size ``group_count`` of number of rows of C on input. Each must be at least 0. n_array Array of size ``group_count`` of number of columns of C on input. Each must be at least 0. alpha_array Array of size ``group_count`` containing scaling factors for the matrix transpositions or copies. matrix_array_in_out Array of size ``total_batch_count``, holding pointers to arrays used to store C matrices. ld_in_array Array of size ``group_count``. The leading dimension of the matrix input ``C``. If matrices are stored using column major layout, ``ld_in_array[i]`` must be at least ``m_array[i]``. If matrices are stored using row major layout, ``ld_in_array[i]`` must be at least ``n_array[i]``. Must be positive. ld_out_array Array of size ``group_count``. The leading dimension of the output matrix ``C``. Each entry ``ld_out_array[i]`` must be positive and at least: - ``m_array[i]`` if column major layout is used and ``C`` is not transposed - ``m_array[i]`` if row major layout is used and ``C`` is transposed - ``n_array[i]`` otherwise 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 matrix_array_in_out Output array of pointers to ``C`` matrices, overwritten by ``total_batch_count`` matrix transpose or copy operations of the form ``alpha*op(C)``. .. 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 imatcopy_batch(sycl::queue &queue, oneapi::mkl::transpose trans, std::int64_t m, std::int64_t n, T alpha, const T *matrix_array_in_out, std::int64_t ld_in, std::int64_t ld_out, std::int64_t stride, std::int64_t batch_size, const std::vector &dependencies = {}); .. code-block:: cpp namespace oneapi::mkl::blas::row_major { sycl::event imatcopy_batch(sycl::queue &queue, oneapi::mkl::transpose trans, std::int64_t m, std::int64_t n, T alpha, const T *matrix_array_in_out, std::int64_t ld_in, std::int64_t ld_out, std::int64_t stride, std::int64_t batch_size, const std::vector &dependencies = {}); .. container:: section .. rubric:: Input Parameters queue The queue where the routine should be executed. trans Specifies ``op(C)``, the transposition operation applied to the matrices C. m Number of rows for each matrix ``C`` on input. Must be at least 0. n Number of columns for each matrix ``C`` on input. Must be at least 0. alpha Scaling factor for the matrix transpose or copy operation. matrix_array_in_out Array holding the matrices ``C``. Must have size at least ``stride*batch_size``. ld_in Leading dimension of the ``C`` matrices on input. If matrices are stored using column major layout, ``ld_in`` must be at least ``m``. If matrices are stored using row major layout, ``ld_in`` must be at least ``n``. Must be positive. ld_out Leading dimension of the ``C`` matrices on output. If matrices are stored using column major layout, ``ld_out`` must be at least ``m`` if ``C`` is not transposed or ``n`` if ``C`` is transposed. If matrices are stored using row major layout, ``ld_out`` must be at least ``n`` if ``C`` is not transposed or at least ``m`` if ``C`` is transposed. Must be positive. stride Stride between different ``C`` matrices within ``matrix_array_in_out``. .. list-table:: :header-rows: 1 * - - ``C`` not transposed - ``C`` transposed * - Column major - ``stride`` must be at least ``max(ld_in*m, ld_out*m)``. - ``stride`` must be at least ``max(ld_in*m, ld_out*n)``. * - Row major - ``stride`` must be at least ``max(ld_in*n, ld_out*n)``. - ``stride`` must be at least ``max(ld_in*n, ld_out*m)``. batch_size Specifies the number of matrices to transpose or copy. dependencies List of events to wait for before starting computation, if any. If omitted, defaults to no dependencies. .. container:: section .. rubric:: Output Parameters matrix_array_in_out Output array, overwritten by ``batch_size`` matrix transposition or copy operations of the form ``alpha*op(C)``. .. 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`