mlr: improving documentation

doc/doxygen/chapters/370_online_performance_tools.doxy

@@ -403,28 +403,30 @@ is based on multiple linear regression. In this model, the user
 defines both the relevant parameters and the equation for computing the
 task duration.
 
+
 \f[
-T_{kernel} = a + b(M^{\alpha_1}\times N^{\beta_1} \times K^{\gamma_1}) + c(M^{\alpha_2}\times N^{\beta_2} \times K^{\gamma_2}) + ...
+T_{kernel} = a + b(M^{\alpha_1} * N^{\beta_1} * K^{\gamma_1}) + c(M^{\alpha_2} * N^{\beta_2} * K^{\gamma_2}) + ...
 \f]
 
+
 \f$M, N, K\f$ are the parameters of the task, added at the task
 creation. These need to be extracted by the <c>cl_perf_func</c>
 function, which should be defined by the user. \f$\alpha, \beta,
-\gamma\f$ are the exponents defined by user in
-<c>model->combinations<\c> matrix. Finally, coefficients $\fa, b, c\f$
+\gamma\f$ are the exponents defined by the user in
+<c>model->combinations</c> table. Finally, coefficients \f$a, b, c\f$
 are computed automatically at the end of the execution, using least
 squares method of the <c>dgels_</c> LAPACK function.
 
 <c>examples/basic_examples/mlr.c</c> example provides more details on
 the usage of ::STARPU_MULTIPLE_REGRESSION_BASED models.
 
-Computing of the coefficient is done at the end of the execution, and
-the results are stored in standard codelet perfmodel files. Additional
-files containing the duration of each task together with the value of
-each parameter is stored in .starpu/sampling/codelets/tmp/
-directory. These files are reused when ::STARPU_CALIBRATE
-environment variable is set to 1, to recompute coefficients based on
-the current, but also on the previous executions.
+Coefficients computation is done at the end of the execution, and the
+results are stored in standard codelet perfmodel files. Additional
+files containing the duration of task together with the value of each
+parameter are stored in <c>.starpu/sampling/codelets/tmp/</c>
+directory. These files are reused when \ref STARPU_CALIBRATE environment
+variable is set to <c>1</c>, to recompute coefficients based on the current,
+but also on the previous executions.
 
 </li>
 

doc/doxygen/chapters/api/performance_model.doxy

@@ -63,7 +63,7 @@ is the type of performance model
 ::STARPU_NL_REGRESSION_BASED: No other fields needs to be provided,
 this is purely history-based.
 </li>
-<li> ::STARPU_MULTIPLE_REGRESSION_BASED: Need to provide fields starpu_perfmodel::nparameters (number of different parameters),  starpu_perfmodel::ncombinations (number of parameters combinations-tuples) and matrix starpu_perfmodel::combinations which defines exponents of the equation. Function cl_perf_func also needs to define how to extract parameters from the task.
+<li> ::STARPU_MULTIPLE_REGRESSION_BASED: Need to provide fields starpu_perfmodel::nparameters (number of different parameters),  starpu_perfmodel::ncombinations (number of parameters combinations-tuples) and table starpu_perfmodel::combinations which defines exponents of the equation. Function cl_perf_func also needs to define how to extract parameters from the task.
 </li>
 <li> ::STARPU_PER_ARCH: either field starpu_perfmodel::arch_cost_function has to be
 filled with a function that returns the cost in micro-seconds on the arch given
@@ -104,6 +104,18 @@ Whether the performance model is already loaded from the disk.
 todo
 \var starpu_perfmodel_state_t starpu_perfmodel::state
 \private
+\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