Moved special 'tuner' key to strategy to avoid invalidating caches

README.md

@@ -38,7 +38,7 @@ There are two entry points defined: `autotuning_experiment` and `autotuning_visu
 
 ### Input files
 To get started, all you need is an experiments file. This is a `json` file that describes the details of your comparison: which algorithms to use, which programs to tune on which devices, the graphs to output and so on. 
-You can find the API and an example `experiments.json` in the [documentation](). 
+You can find the API and an example `experiments.json` in the [documentation](https://autotuningassociation.github.io/autotuning_methodology/modules.html). 
 
 ### File references
 As we are dealing with input and output files, file references matter. 

tests/autotuning_methodology/integration/mockfiles/test.json

@@ -41,7 +41,6 @@
         "compare_split_times": true
     },
     "strategy_defaults": {
-        "tuner": "kerneltuner",
         "repeats": 10,
         "minimum_number_of_evaluations": 20,
         "stochastic": true,

tests/autotuning_methodology/integration/mockfiles/test_bad_kernel_path.json

@@ -50,7 +50,6 @@
     "strategies": [
         {
             "name": "random_sample_100_iter",
-            "tuner": "kerneltuner",
             "strategy": "random_sample",
             "display_name": "Random sampling 100 iters",
             "repeats": 5

tests/autotuning_methodology/integration/mockfiles/test_cached.json

@@ -39,7 +39,6 @@
         "compare_split_times": false
     },
     "strategy_defaults": {
-        "tuner": "kerneltuner",
         "repeats": 100,
         "minimum_number_of_evaluations": 20,
         "stochastic": true,