Merge branch 'mm_reorganisation' of github.com:UCL/research-computing…

…-with-cpp into mm_reorganisation

07performance/index.md

@@ -8,19 +8,19 @@ This week we'll be introducing some concepts for producing high performance prog
 
 Even though parallelism can help us improve our throughput, single core optimisation is still vital for producing good performance on ordinary machines or for maximising the work that each core can do in a parallel program. This week we'll talk about:
 
-1. [_Why_ and _when_ we should optimise](sec00Motivation)
-2. [Complexity and algorithm analysis](sec01Complexity) 
+1. [_Why_ and _when_ we should optimise](sec00Motivation.html)
+2. [Complexity and algorithm analysis](sec01Complexity.html) 
     - How the time and space usage of algorithms scales with the size of the input. 
     - Big-O notation.
     - How to determine complexity and examples with some common algorithms.
     - How does complexity impact our choices as software designers?
-3. [Memory management and caching](sec02Memory)
+3. [Memory management and caching](sec02Memory.html)
     - Memory bound problems. 
     - How memory is structured in a typical machine.
     - Speed of different kinds of memory access.
     - Cache structure and operation. 
     - Writing algorithms to effectively exploit the cache. 
-4. [Compiler Optimisation](sec03Optimisation)
+4. [Compiler Optimisation](sec03Optimisation.html)
     - Automated optimisation by the compiler. 
     - Compiler flags for optimisation.
     - Examples of optimisations, pros and cons.