1.e-Performance-hazards.md

 There are many things that can limit the performance we achieve. 
+A general overview of different GPU performance bottlenecks is given in the section below.
 In order to overcome these issues, there are some debugging tools that can be of help.
-First, a general overview of different GPU performance bottlenecks is given.
-Then a list of tools to combat these bottlenecks will be discussed.
+These are discussed in the previous section [1.d. Profiling](1.d-Profiling).
 
 ## Potential problems
 There are 6 general problems that can limit the performance of GPUs.
@@ -54,12 +54,4 @@ There is also some implicit behavior by OpenMP which can penalize performance.
 The list below are the ones we know of, but there might be more:
 
 **Array copying**  
-If an array is copied (`a=b`, `a(:,:,:) = b(:,:,:)`, etc.) within an `$omp target parallel do`, all threads will perform this copy.
-
+If an array is copied (`a=b`, `a(:,:,:) = b(:,:,:)`, etc.) within an `$omp target parallel do`, all threads will perform this copy.
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-## Debug tools
-Many things discussed here are an extension to the previous section [1.d. Profiling](1.d-Profiling).
-Please refer to that page for specifics on how to use the tools.
-
-Debugging is possible at compiler time or at runtime.
-The options are compiler and hardware vendor specific, so that distinction will be made first.
-Then in their subsections, the different compiler and runtime diagnostics will be discussed.
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