mlr: writing nan when model is unknown

src/core/perfmodel/multiple_regression.c

@@ -243,15 +243,15 @@ int dgels_multiple_reg_coeff(double *mpar, double *my, long nn, unsigned ncoeff,
    Validating the accuracy of the coefficients.
    For the the validation is extremely basic, but it should be improved.
  */
-void validate(double *coeff, unsigned ncoeff)
+void validate(double *coeff, unsigned ncoeff, const char *codelet_name)
 {
 	unsigned i;
 	if (coeff[0] < 0)
-		_STARPU_DISP("Warning: Constant computed by least square method is negative (%f). The model is likely to be inaccurate.\n", coeff[0]);
+		_STARPU_DISP("Warning: Constant computed by least square method is negative (%f). The model %s is likely to be inaccurate.\n", coeff[0], codelet_name);
 		
 	for(i=1; i<ncoeff; i++)
 		if(coeff[i] < 1E-10)
-			_STARPU_DISP("Warning: Coefficient computed by least square method is extremelly small (%f). The model is likely to be inaccurate.\n", coeff[i]);
+			_STARPU_DISP("Warning: Coefficient computed by least square method is extremelly small (%f). The model %s is likely to be inaccurate.\n", coeff[i], codelet_name);
 }
 	
 int _starpu_multiple_regression(struct starpu_perfmodel_history_list *ptr, double *coeff, unsigned ncoeff, unsigned nparameters, const char **parameters_names, unsigned **combinations, const char *codelet_name)
@@ -260,6 +260,8 @@ int _starpu_multiple_regression(struct starpu_perfmodel_history_list *ptr, doubl
 	unsigned j;
 #ifndef STARPU_MLR_MODEL
 	_STARPU_DISP("Warning: StarPU was compiled with '--disable-mlr' option or on Windows machine, thus multiple linear regression model will not be computed.\n");
+	if (ncoeff==0 || combinations==NULL)
+		return 2;
 	for(i=0; i<ncoeff; i++)
 		coeff[i] = 0.;
 	return 1;
@@ -308,14 +310,17 @@ int _starpu_multiple_regression(struct starpu_perfmodel_history_list *ptr, doubl
 	/* Filling X and Y matrices with measured values */
 	dump_multiple_regression_list(mpar, my, old_lines, nparameters, ptr);
 
+	if (ncoeff!=0 && combinations!=NULL)
+	{
 #ifdef STARPU_MLR_MODEL
-	/* Computing coefficients using multiple linear regression */
-	if(dgels_multiple_reg_coeff(mpar, my, n, ncoeff, nparameters, coeff, combinations))
+		/* Computing coefficients using multiple linear regression */
+		if(dgels_multiple_reg_coeff(mpar, my, n, ncoeff, nparameters, coeff, combinations))
 		return 1;
 #endif //STARPU_MLR_MODEL
 
-	/* Basic validation of the model accuracy */
-	validate(coeff, ncoeff);
+		/* Basic validation of the model accuracy */
+		validate(coeff, ncoeff, codelet_name);
+	}
 	
 	/* Preparing new output calibration file */
 	if (calibrate==1 || calibrate==2)

src/core/perfmodel/perfmodel_history.c

@@ -292,8 +292,10 @@ static void dump_reg_model(FILE *f, struct starpu_perfmodel *model, int comb, in
 
 	if (model->type == STARPU_MULTIPLE_REGRESSION_BASED)
 	{
-		if (reg_model->ncoeff==0)
+		if (reg_model->ncoeff==0 && model->ncombinations!=0 && model->combinations!=NULL)
+		{
 			reg_model->ncoeff = model->ncombinations + 1;
+		}
 
 		reg_model->coeff = (double *) malloc(reg_model->ncoeff*sizeof(double));
 		_starpu_multiple_regression(per_arch_model->list, reg_model->coeff, reg_model->ncoeff, model->nparameters, model->parameters_names, model->combinations, model->symbol);
@@ -301,39 +303,43 @@ static void dump_reg_model(FILE *f, struct starpu_perfmodel *model, int comb, in
 		fprintf(f, "# n\tintercept\t");
 	        unsigned i, j;
 		int first;
-		for (i=0; i < model->ncombinations; i++)
+		if (reg_model->ncoeff==0 || model->ncombinations==0 || model->combinations==NULL)
+			fprintf(f, "\n1\tnan");
+		else
 		{
-			if (model->parameters_names == NULL)
-				fprintf(f, "c%d", i+1);
-			else
+			for (i=0; i < model->ncombinations; i++)
 			{
-				first=1;
-				for(j=0; j < model->nparameters; j++)
+				if (model->parameters_names == NULL)
+					fprintf(f, "c%d", i+1);
+				else
 				{
-					if (model->combinations[i][j] > 0)
+					first=1;
+					for(j=0; j < model->nparameters; j++)
 					{
-						if (first)
-							first=0;
-						else
-							fprintf(f, "*");
+						if (model->combinations[i][j] > 0)
+						{
+							if (first)
+								first=0;
+							else
+								fprintf(f, "*");
 						
-						if(model->parameters_names[j]!= NULL)
-							fprintf(f, "%s", model->parameters_names[j]);
-						else
-							fprintf(f, "P%d", j);
+							if(model->parameters_names[j] != NULL)
+								fprintf(f, "%s", model->parameters_names[j]);
+							else
+								fprintf(f, "P%d", j);
 						
-						if (model->combinations[i][j] > 1)
-							fprintf(f, "^%d", model->combinations[i][j]);
+							if (model->combinations[i][j] > 1)
+								fprintf(f, "^%d", model->combinations[i][j]);
+						}
 					}
 				}
+				fprintf(f, "\t\t");
 			}
-			fprintf(f, "\t\t");
-		}
-
-		fprintf(f, "\n%u", reg_model->ncoeff);
-		for (i=0; i < reg_model->ncoeff; i++)
-			fprintf(f, "\t%-15e", reg_model->coeff[i]);
 
+			fprintf(f, "\n%u", reg_model->ncoeff);
+			for (i=0; i < reg_model->ncoeff; i++)
+				fprintf(f, "\t%-15e", reg_model->coeff[i]);
+		}
 	}
 }
 #endif
@@ -1323,7 +1329,7 @@ double _starpu_multiple_regression_based_job_expected_perf(struct starpu_perfmod
 	reg_model = &model->state->per_arch[comb][nimpl].regression;
 	if (reg_model->coeff == NULL)
 		goto docal;
-
+	
 	double parameter_value;
 	double *parameters;
 	parameters = (double *) malloc(model->nparameters*sizeof(double));