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mlr: cosmetics

Luka Stanisic 9 年之前
父节点
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e6c455a530
共有 2 个文件被更改,包括 7 次插入8 次删除
  1. 5 8
      examples/basic_examples/mlr.c
  2. 2 0
      tools/starpu_mlr_analysis.Rmd

+ 5 - 8
examples/basic_examples/mlr.c

@@ -19,18 +19,15 @@
  * This examples demonstrates how to use multiple linear regression
  * This examples demonstrates how to use multiple linear regression
    models.
    models.
 
 
-   First, there is cl_model_init codelet for which we know the
+   First, there is mlr_codelet__init codelet for which we know the
    parameters, but not the their exponents and relations. This tasks
    parameters, but not the their exponents and relations. This tasks
    should be benchmarked and analyzed to find the model, using
    should be benchmarked and analyzed to find the model, using
-   "tools/starpu_mlr_analysis" script as a template. Before the model
-   is defined by the application developer, the default model is
-   automatically computed. This default models is a simple constant
-   (thus making STARPU_MULTIPLE_REGRESSION_BASED model equal to the
-   history based model).
+   "tools/starpu_mlr_analysis" script as a template.
 
 
    For the second (codelet cl_model_final), it is assumed that the
    For the second (codelet cl_model_final), it is assumed that the
-   analysis has already been performend and that he duration of the
-   task test_mlr will be computed using the following equation:
+   analysis has already been performed and that the duration of the
+   codelet mlr_codelet_final will be computed using the following
+   equation:
 
 
    T = a + b * (M^2*N) + c * (N^3*K)
    T = a + b * (M^2*N) + c * (N^3*K)
 
 

+ 2 - 0
tools/starpu_mlr_analysis.Rmd

@@ -54,6 +54,8 @@ print_codelet <- function(reg,codelet){
 }
 }
 
 
 df<-read.csv(input_trace, header=TRUE)
 df<-read.csv(input_trace, header=TRUE)
+
+opts_chunk$set(echo=TRUE)
 ```
 ```
 
 
 # Multiple Linear Regression Model Example
 # Multiple Linear Regression Model Example