#ifndef LOOP_CUDA_HH #define LOOP_CUDA_HH #include "loop.hh" #include #include enum MemoryMode { GlobalMem, SharedMem, TexMem }; //protonu --class introduced to hold texture memory information in one single place //this might help me get over the weird memory issues I am having with the Loop class //where someone/something corrupts my memory class texture_memory_mapping{ private: bool tex_mem_used; std::vector< std::string > tex_mapped_array_name; public: texture_memory_mapping ( bool used, const char * array_name){ tex_mem_used = used; tex_mapped_array_name.push_back(std::string(array_name)); } void add(const char * array_name) { tex_mapped_array_name.push_back(std::string(array_name)); } bool is_tex_mem_used() {return tex_mem_used;} bool is_array_tex_mapped(const char * array_name){ for( int i=0; i cons_mapped_array_name; public: constant_memory_mapping ( bool used, const char * array_name){ cons_mem_used = used; cons_mapped_array_name.push_back(std::string(array_name)); } void add(const char * array_name) { cons_mapped_array_name.push_back(std::string(array_name)); } bool is_cons_mem_used() {return cons_mem_used;} bool is_array_cons_mapped(const char * array_name){ for( int i=0; i new_procs; //Need adding to a fse std::vector< std::vector > idxNames; std::vector< std::pair > syncs; bool useIdxNames; std::vector index; proc_symtab *symtab; global_symtab *globals; //protonu--inserting this here, Gabe's implementation had it //the struct statment as nonSplitLevels std::vector > stmt_nonSplitLevels; texture_memory_mapping *texture; //protonu constant_memory_mapping *constant_mem; //protonu std::map array_dims; omega::CG_outputRepr *setup_code; omega::CG_outputRepr *teardown_code; unsigned int code_gen_flags; enum CodeGenFlags { GenInit = 0x00, GenCudaizeV2 = 0x02, }; //varibles used by cudaize_codegen //block x, y sizes, N and num_red int cu_bx, cu_by, cu_n, cu_num_reduce; //block statement and level int cu_block_stmt, cu_block_level; //thread x, y, z int cu_tx, cu_ty, cu_tz; //tile statements, and loop-levels (cudaize v1) std::vector< std::vector > cu_thread_loop; std::vector cu_thread_sync; MemoryMode cu_mode; std::string cu_nx_name, cu_ny_name, cu_kernel_name; int nonDummyLevel(int stmt, int level); bool symbolExists(std::string s); void addSync(int stmt, std::string idx); void renameIndex(int stmt, std::string idx, std::string newName); bool validIndexes(int stmt, const std::vector& idxs); void extractCudaUB(int stmt_num, int level, int &outUpperBound, int &outLowerBound); void printCode(int effort=1, bool actuallyPrint=true) const; void printRuntimeInfo() const; void printIndexes() const; tree_node_list* getCode(int effort = 1) const; void permute_cuda(int stmt, const std::vector& curOrder); //protonu-writing a wrapper for the Chun's new permute function bool permute(int stmt_num, const std::vector &pi); //end--protonu. void tile_cuda(int stmt, int level, int outer_level); void tile_cuda(int level, int tile_size, int outer_level, std::string idxName, std::string ctrlName, TilingMethodType method=StridedTile); void tile_cuda(int stmt, int level, int tile_size, int outer_level, std::string idxName, std::string ctrlName, TilingMethodType method=StridedTile); bool datacopy_privatized_cuda(int stmt_num, int level, const std::string &array_name, const std::vector &privatized_levels, bool allow_extra_read = false, int fastest_changing_dimension = -1, int padding_stride = 1, int padding_alignment = 1, bool cuda_shared=false); bool datacopy_cuda(int stmt_num, int level, const std::string &array_name, std::vector new_idxs, bool allow_extra_read = false, int fastest_changing_dimension = -1, int padding_stride = 1, int padding_alignment = 4, bool cuda_shared=false); bool unroll_cuda(int stmt_num, int level, int unroll_amount); //protonu--using texture memory void copy_to_texture(const char *array_name); //protonu--using constant memory void copy_to_constant(const char *array_name); int findCurLevel(int stmt, std::string idx); /** * * @param kernel_name Name of the GPU generated kernel * @param nx Iteration space over the x dimention * @param ny Iteration space over the y dimention * @param tx Tile dimention over x dimention * @param ty Tile dimention over the y dimention * @param num_reduce The number of dimentions to reduce by mapping to the GPU implicit blocks/threads */ //stmnt_num is referenced from the perspective of being inside the cudize block loops bool cudaize_v2(std::string kernel_name, std::map array_dims, std::vector blockIdxs, std::vector threadIdxs); tree_node_list* cudaize_codegen_v2(); tree_node_list* codegen(); //protonu--have to add the constructors for the new class //and maybe destructors (?) LoopCuda(); //LoopCuda(IR_Code *ir, tree_for *tf, global_symtab* gsym); LoopCuda(IR_Control *ir_c, int loop_num);//protonu-added so as to not change ir_suif ~LoopCuda(); }; #endif