concept and design: improved wording and added overview diagram of kernel usage

thesis/chapters/relwork.tex

@@ -126,6 +126,7 @@ Additionally, shared memory consumption can also impact the occupancy. If for ex
 Balancing these limitations and therefore the occupancy and performance often requires a lot of trial and error with help of the aforementioned tools. In cases where occupancy is already high and the amount of warps ready for execution is also high, other areas for performance improvements need to be explored. Algorithmic optimisation is always a good idea. Some performance improvements can be achieved by altering the computations to use different parts of the GPU. One of such optimisations is using FP32 operations wherever possible. Another well suited optimisation is to rewrite the algorithm to use as many Fused Multiply-Add (FMA) instructions. FMA is a special floating point instruction, that multiplies two values and adds a third, all in a single clock cycle \parencite{nvidia_cuda_2025-1}. However, the result might slightly deviate compared to performing these two operations separately, which means in accuracy sensitive scenarios, this instruction should be avoided. If the compiler detects a floating point operation with the FMA structure, it will automatically be compiled to an FMA instruction. To prevent this, in C++ the developer can call the functions \_\_fadd\_ and \_\_fmul\_ for addition and multiplication respectively.
 
 \subsection[PTX]{Parallel Thread Execution}
+\label{sec:ptx}
 % https://docs.nvidia.com/cuda/parallel-thread-execution/
 While in most cases a GPU can be programmed in a higher level language like C++ or even Julia\footnote{\url{https://juliagpu.org/}}, it is also possible to program GPUs with the low level language Parallel Thread Execution (PTX) developed by Nvidia. A brief overview of what PTX is and how it can be used to program GPUs is given in this section. Information in this section is taken from the PTX documentation \parencite{nvidia_parallel_2025} if not stated otherwise.