Mir 1.0
Mir application programming interface
Data Structures
Here are the data structures with brief descriptions:
 Cmir_arg_iter_t
 Cmir_defarg_t
 Cmir_dimp_t_
 Cmir_idata_t_
 Cmir_module_symbol_t_This structure is used to assign symbol names to module pointers
 Cmir_module_t_
 Cmir_obj_var_dsynch_data_t_
 Cmir_obj_var_dsynch_t_
 Cmirkl_arr_t_Multidimensional array
 Cmirkl_bitarr_t_Structure of bit array
 Cmirkl_cdllist_t_Structure of Double-Linked Cached List
 Cmirkl_cpu_cache_t_
 Cmirkl_cpu_core_t_
 Cmirkl_cpu_hwt_t_
 Cmirkl_cpu_pkg_t_
 Cmirkl_cpu_t_
 Cmirkl_dir_trctx_t_Traverse context. Data in this structure control traversing of directories
 Cmirkl_dllist_t_Structure of Double-Linked List
 Cmirkl_error_t_Structure of error object
 Cmirkl_image_t_
 Cmirkl_log_t_
 Cmirkl_pdata_t_
 Cmirkl_pval_t_
 Cmirkl_readline_t_
 Cmirkl_sha1_ctx_t_SHA1 context
 Cmirkl_sllist_t_
 Cmirkl_stack_t_Stack structure
 Cmirkl_str_list_t_List of strings
 Cmirkl_tree_t_
 Cmirkl_trie_t_
 Cmirm_example_t_
 Cmirm_image_t_Image data structure
 Cmirml_complex_float_t_
 Cmirml_complex_ldouble_t_
 Cmirml_complex_t_
 Cmirml_dtype_t_
 Cmirml_fsampler_1d_optionsControl options for 1d-fsampler
 Cmirml_lsq_t_Context for least squares procedures
 Cmirml_matrix_t_Matrix definition
 Cmirml_membw_ctx_t_Context for memory bandwidth benchmarking
 Cmirml_memlat_ctx_t_Context for memory latency benchmarking
 Cmirml_mh_bandm_t_Band matrix definition
 Cmirml_mh_i64vector_t_Vector of 64-bit integer numbers
 Cmirml_mh_iter_t_Basic structure for iterative methods
 Cmirml_mh_ivector_t_Vector of integer numbers
 Cmirml_mh_matrix_t_Matrix definition
 Cmirml_mh_permutation_t_Permutation definition
 Cmirml_mh_row_elt_t_Element of row in sparse matrices
 Cmirml_mh_spmatrix_t_Sparse matrix
 Cmirml_mh_sprow_t_Row in sparse matrices
 Cmirml_mh_vector_t_
 Cmirml_nr_gammadev_t_Generator of random deviates with gamma distribution
 Cmirml_nr_itpl_t_Interpolation structure
 Cmirml_nr_jtsm_t_Structure for Jacobi transformations of symmetric matrices
 Cmirml_nr_svd_t_Structure for Singular Value Decomposition (SVD) of matrices: A=U*W*V^T
 Cmirml_rsamp_incr_t_Structure for online incremental calculation of sample statistics
 Cmirml_vector_t_Vector definition
 Cmirmpiw_status_t