Abstract
A parallel processing system's most crucial part is a network interconnection that links its processors. The hypercube topology has exciting features, making it an excellent option for parallel processing applications. This paper presents two innovative configurations of interconnection networks based on fractal Sierpinski and a hypercube. These are the Sierpinski Triangle Topology (STT) and Sierpinski Carpet Topology (SCT). Compared to a hypercube, the Sierpinski Triangle topology (STT) noticed a significant decrease in the number of nodes and links as large networks grew. Hence, it considers a great way to reduce costs because it uses fewer nodes and links. The average distance is also shorter, which is better. Despite it has a smaller bisection width and a more degree than a hypercube by one. The Sierpinski Carpet Topology (SCT) has the advantage of having a higher bisection width than a hypercube. That is preferable because it places a lower restriction on the difficulty of parallel algorithms. In contrast, the drawback of this topology is that it has a diameter and average distance more than a hypercube.
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