## 5 Experiments
### Use-Cases  
In this section, two different use-cases and various possible mappings were considered to evaluate the efficiency of the created models in terms of accuracy and analysis time. For every considered use-cases and mappings we predicted the average iteration delay of the application, as well as the possible distribution of execution times. We executed all these experiments on a real platform and measured the actual execution times of each iteration. The obtained predictions were compared between simulation and measured results.  
We compare the simulation results from the Cycle Accurate communication model first introduced in [5], the Message Level model proposed in [6] and the Transaction Level model. In Figure 2b,c, we present the applications to validate our proposed approach. In Figure 2a our heterogeneous multiprocessor system that was used for all the experiments is shown. In our experiments, we considered two SDF applications to validate our proposed approach:  
The _Sobel-Filter_ (see Figure 2b) which comes with simple compute phases and relatively high communication delays, is used to stress the communication models. Due to the low computational part of this application, errors in the communication model become more visible. In this use-case, the communication part takes most of the execution time. When we executed the application on tiles with an hardware multiplier, the computation part is highly predictable. In contrast to the JPEG-Decoder, the execution paths of the Sobel-Filter can be identified manually For the _GetPixel_ actor, there were 9 execution paths depending on the position of tokens (\(3\times 3\) pixels matrix) in the image. The _ABS_ actor has 4 execution paths depending on the input tokens. There is only one execution path for _GX_ and _GY_ actors. We used a noise image as input of these Sobel-experiments. The analysis results of this application show the validation of our proposed communication model. We used the noise image as input of the applications. The image has a size of \(48\times 48\) Pixels  
The _JPEG-Decoder_ (see Figure 2c) with a wide range of possible execution times an relatively short communication delays is used to stress the computation models because errors in the communication model have a low impact on the simulation results. This use-case presents a huge computation part with an unknown and unmanageable amount of execution paths in most of the actors except for the IQ-actors that contain only one execution path when using hardware multiplier.  
For each use-case different mappings were applied as shown in Table 1. The experiment name consists of the Use-Case application, the used communication model, and the amount of processing elements used for the mapping. We simulated these mappings with different communication and computation models as shown in Figure 6. We simulated 3 mappings for Sobel Filter: _Sobel-1_, _Sobel-2_ and _Sobel-4_. For JPEG Decoder, we also considered 3 mappings: _JPEG-1_, _JPEG-3_ and _JPEG-7_. For each Use-Case and mapping, the different communication models _CA_ (Cycle Accurate), _TL_ (Transaction Level) and _ML_ (Message Level) are used, as well as the different computation models _Avg_ (Average), _Gauss_ (Gaussian Distribution) and _KDE_ (Kernel Density Estimation).  
For all the experiments the instruction and local data of an actor were mapped on the private memory of a tile. The applications are executed without any operating system. Interrupts are disabled so that it is guaranteed that there is no preemption. All buffers are static allocated. There is no dynamic memory management. The scheduling of the actors is static as well.