/* StarPU --- Runtime system for heterogeneous multicore architectures. * * Copyright (C) 2011-2013,2016 Inria * Copyright (C) 2010-2017 CNRS * Copyright (C) 2009-2011,2013-2017 Université de Bordeaux * * StarPU is free software; you can redistribute it and/or modify * it under the terms of the GNU Lesser General Public License as published by * the Free Software Foundation; either version 2.1 of the License, or (at * your option) any later version. * * StarPU is distributed in the hope that it will be useful, but * WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. * * See the GNU Lesser General Public License in COPYING.LGPL for more details. */ /*! \defgroup API_Performance_Model Performance Model \enum starpu_perfmodel_type \ingroup API_Performance_Model TODO \var starpu_perfmodel_type::STARPU_PERFMODEL_INVALID todo \var starpu_perfmodel_type::STARPU_PER_ARCH Application-provided per-arch cost model function \var starpu_perfmodel_type::STARPU_COMMON Application-provided common cost model function, with per-arch factor \var starpu_perfmodel_type::STARPU_HISTORY_BASED Automatic history-based cost model \var starpu_perfmodel_type::STARPU_REGRESSION_BASED Automatic linear regression-based cost model (alpha * size ^ beta) \var starpu_perfmodel_type::STARPU_NL_REGRESSION_BASED Automatic non-linear regression-based cost model (a * size ^ b + c) \var starpu_perfmodel_type::STARPU_MULTIPLE_REGRESSION_BASED Automatic multiple linear regression-based cost model. Application provides parameters, their combinations and exponents. \struct starpu_perfmodel_device todo \ingroup API_Performance_Model \var enum starpu_worker_archtype starpu_perfmodel_device::type type of the device \var int starpu_perfmodel_device::devid identifier of the precise device \var int starpu_perfmodel_device::ncore number of execution in parallel, minus 1 \struct starpu_perfmodel_arch todo \ingroup API_Performance_Model \var int starpu_perfmodel_arch::ndevices number of the devices for the given arch \var struct starpu_perfmodel_device *starpu_perfmodel_arch::devices list of the devices for the given arch \struct starpu_perfmodel Contain all information about a performance model. At least the type and symbol fields have to be filled when defining a performance model for a codelet. For compatibility, make sure to initialize the whole structure to zero, either by using explicit memset, or by letting the compiler implicitly do it in e.g. static storage case. If not provided, other fields have to be zero. \ingroup API_Performance_Model \var enum starpu_perfmodel_type starpu_perfmodel::type type of performance model \var const char *starpu_perfmodel::symbol symbol name for the performance model, which will be used as file name to store the model. It must be set otherwise the model will be ignored. \var double (*starpu_perfmodel::cost_function)(struct starpu_task *, unsigned nimpl) Used by ::STARPU_COMMON. Take a task and implementation number, and must return a task duration estimation in micro-seconds. \var double (*starpu_perfmodel::arch_cost_function)(struct starpu_task *, struct starpu_perfmodel_arch* arch, unsigned nimpl) Used by ::STARPU_COMMON. Take a task, an arch and implementation number, and must return a task duration estimation in micro-seconds on that arch. \var size_t (*starpu_perfmodel::size_base)(struct starpu_task *, unsigned nimpl) Used by ::STARPU_HISTORY_BASED, ::STARPU_REGRESSION_BASED and ::STARPU_NL_REGRESSION_BASED. If not NULL, take a task and implementation number, and return the size to be used as index to distinguish histories and as a base for regressions. \var uint32_t (*starpu_perfmodel::footprint)(struct starpu_task *) Used by ::STARPU_HISTORY_BASED. If not NULL, take a task and return the footprint to be used as index to distinguish histories. The default is to use the starpu_task_data_footprint() function. \var unsigned starpu_perfmodel::is_loaded \private Whether the performance model is already loaded from the disk. \var unsigned starpu_perfmodel::benchmarking \private todo \var unsigned starpu_perfmodel::is_init todo \var starpu_perfmodel_state_t starpu_perfmodel::state \private todo \var void (*starpu_perfmodel::parameters)(struct starpu_task * task, double *parameters); todo \var const char ** starpu_perfmodel::parameters_names \private Names of parameters used for multiple linear regression models (M, N, K) \var unsigned starpu_perfmodel::nparameters \private Number of parameters used for multiple linear regression models \var unsigned ** starpu_perfmodel::combinations \private Table of combinations of parameters (and the exponents) used for multiple linear regression models \var unsigned starpu_perfmodel::ncombinations \private Number of combination of parameters used for multiple linear regression models \struct starpu_perfmodel_regression_model todo \ingroup API_Performance_Model \var double starpu_perfmodel_regression_model::sumlny sum of ln(measured) \var double starpu_perfmodel_regression_model::sumlnx sum of ln(size) \var double starpu_perfmodel_regression_model::sumlnx2 sum of ln(size)^2 \var unsigned long starpu_perfmodel_regression_model::minx minimum size \var unsigned long starpu_perfmodel_regression_model::maxx maximum size \var double starpu_perfmodel_regression_model::sumlnxlny sum of ln(size)*ln(measured) \var double starpu_perfmodel_regression_model::alpha estimated = alpha * size ^ beta \var double starpu_perfmodel_regression_model::beta estimated = alpha * size ^ beta \var unsigned starpu_perfmodel_regression_model::valid whether the linear regression model is valid (i.e. enough measures) \var double starpu_perfmodel_regression_model::a estimated = a size ^b + c \var double starpu_perfmodel_regression_model::b estimated = a size ^b + c \var double starpu_perfmodel_regression_model::c estimated = a size ^b + c \var unsigned starpu_perfmodel_regression_model::nl_valid whether the non-linear regression model is valid (i.e. enough measures) \var unsigned starpu_perfmodel_regression_model::nsample number of sample values for non-linear regression \var double starpu_perfmodel_regression_model::coeff[] list of computed coefficients for multiple linear regression model \var double starpu_perfmodel_regression_model::ncoeff number of coefficients for multiple linear regression model \var double starpu_perfmodel_regression_model::multi_valid whether the multiple linear regression model is valid \struct starpu_perfmodel_per_arch contains information about the performance model of a given arch. \ingroup API_Performance_Model \var starpu_perfmodel_per_arch_cost_function starpu_perfmodel_per_arch::cost_function Used by ::STARPU_PER_ARCH, must point to functions which take a task, the target arch and implementation number (as mere conveniency, since the array is already indexed by these), and must return a task duration estimation in micro-seconds. \var starpu_perfmodel_per_arch_size_base starpu_perfmodel_per_arch::size_base Same as in structure starpu_perfmodel, but per-arch, in case it depends on the architecture-specific implementation. \var struct starpu_perfmodel_history_table *starpu_perfmodel_per_arch::history \private The history of performance measurements. \var struct starpu_perfmodel_history_list *starpu_perfmodel_per_arch::list \private Used by ::STARPU_HISTORY_BASED, ::STARPU_NL_REGRESSION_BASED and ::STARPU_MULTIPLE_REGRESSION_BASED, records all execution history measures. \var struct starpu_perfmodel_regression_model starpu_perfmodel_per_arch::regression \private Used by ::STARPU_REGRESSION_BASED, ::STARPU_NL_REGRESSION_BASED and ::STARPU_MULTIPLE_REGRESSION_BASED, contains the estimated factors of the regression. \struct starpu_perfmodel_history_list todo \ingroup API_Performance_Model \var struct starpu_perfmodel_history_list *starpu_perfmodel_history_list::next todo \var struct starpu_perfmodel_history_entry *starpu_perfmodel_history_list::entry todo \struct starpu_perfmodel_history_entry todo \ingroup API_Performance_Model \var double starpu_perfmodel_history_entry::mean mean_n = 1/n sum \var double starpu_perfmodel_history_entry::deviation n dev_n = sum2 - 1/n (sum)^2 \var double starpu_perfmodel_history_entry::sum sum of samples (in µs) \var double starpu_perfmodel_history_entry::sum2 sum of samples^2 \var unsigned starpu_perfmodel_history_entry::nsample number of samples \var uint32_t starpu_perfmodel_history_entry::footprint data footprint \var size_t starpu_perfmodel_history_entry::size in bytes \var double starpu_perfmodel_history_entry::flops Provided by the application \fn void starpu_perfmodel_init(struct starpu_perfmodel *model) \ingroup API_Performance_Model todo \fn void starpu_perfmodel_free_sampling_directories(void) \ingroup API_Performance_Model Free internal memory used for sampling directory management. It should only be called by an application which is not calling starpu_shutdown() as this function already calls it. See for example tools/starpu_perfmodel_display.c. \fn int starpu_perfmodel_load_file(const char *filename, struct starpu_perfmodel *model) \ingroup API_Performance_Model Load the performance model found in the file named \p filename. \p model has to be completely zero, and will be filled with the information stored in the given file. \fn int starpu_perfmodel_load_symbol(const char *symbol, struct starpu_perfmodel *model) \ingroup API_Performance_Model Load a given performance model. \p model has to be completely zero, and will be filled with the information stored in $STARPU_HOME/.starpu. The function is intended to be used by external tools that want to read the performance model files. \fn int starpu_perfmodel_unload_model(struct starpu_perfmodel *model) \ingroup API_Performance_Model Unload \p model which has been previously loaded through the function starpu_perfmodel_load_symbol() \fn void starpu_perfmodel_debugfilepath(struct starpu_perfmodel *model, struct starpu_perfmodel_arch *arch, char *path, size_t maxlen, unsigned nimpl) \ingroup API_Performance_Model Return the path to the debugging information for the performance model. \fn char* starpu_perfmodel_get_archtype_name(enum starpu_worker_archtype archtype) \ingroup API_Performance_Model todo \fn void starpu_perfmodel_get_arch_name(struct starpu_perfmodel_arch *arch, char *archname, size_t maxlen, unsigned nimpl) \ingroup API_Performance_Model Return the architecture name for \p arch \fn struct starpu_perfmodel_arch *starpu_worker_get_perf_archtype(int workerid, unsigned sched_ctx_id) \ingroup API_Performance_Model Return the architecture type of the worker \p workerid. \fn void starpu_perfmodel_initialize(void) \ingroup API_Performance_Model If starpu_init is not used, starpu_perfmodel_initialize should be used before calling starpu_perfmodel_* functions. \fn int starpu_perfmodel_list(FILE *output) \ingroup API_Performance_Model Print a list of all performance models on \p output \fn void starpu_perfmodel_directory(FILE *output) \ingroup API_Performance_Model Print the directory name storing performance models on \p output \fn void starpu_perfmodel_print(struct starpu_perfmodel *model, struct starpu_perfmodel_arch *arch, unsigned nimpl, char *parameter, uint32_t *footprint, FILE *output) \ingroup API_Performance_Model todo \fn int starpu_perfmodel_print_all(struct starpu_perfmodel *model, char *arch, char *parameter, uint32_t *footprint, FILE *output) \ingroup API_Performance_Model todo \fn int starpu_perfmodel_print_estimations(struct starpu_perfmodel *model, uint32_t footprint, FILE *output) \ingroup API_Performance_Model todo \fn void starpu_bus_print_bandwidth(FILE *f) \ingroup API_Performance_Model Print a matrix of bus bandwidths on \p f. \fn void starpu_bus_print_affinity(FILE *f) \ingroup API_Performance_Model Print the affinity devices on \p f. \fn void starpu_bus_print_filenames(FILE *f) \ingroup API_Performance_Model Print on \p f the name of the files containing the matrix of bus bandwidths, the affinity devices and the latency. \fn void starpu_perfmodel_update_history(struct starpu_perfmodel *model, struct starpu_task *task, struct starpu_perfmodel_arch *arch, unsigned cpuid, unsigned nimpl, double measured); \ingroup API_Performance_Model Feed the performance model model with an explicit measurement measured (in µs), in addition to measurements done by StarPU itself. This can be useful when the application already has an existing set of measurements done in good conditions, that StarPU could benefit from instead of doing on-line measurements. An example of use can be seen in \ref PerformanceModelExample. \fn double starpu_transfer_bandwidth(unsigned src_node, unsigned dst_node) \ingroup API_Performance_Model Return the bandwidth of data transfer between two memory nodes \fn double starpu_transfer_latency(unsigned src_node, unsigned dst_node) \ingroup API_Performance_Model Return the latency of data transfer between two memory nodes \fn double starpu_transfer_predict(unsigned src_node, unsigned dst_node, size_t size) \ingroup API_Performance_Model Return the estimated time to transfer a given size between two memory nodes. \fn double starpu_perfmodel_history_based_expected_perf(struct starpu_perfmodel *model, struct starpu_perfmodel_arch* arch, uint32_t footprint) \ingroup API_Performance_Model Return the estimated time of a task with the given model and the given footprint. \var starpu_perfmodel_nop Performance model which just always return 1µs. */