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A parallel processing system's most crucial part is a network interconnection that links its processors. The hypercube topology has interesting features that make it a great option for parallel processing applications. This paper presents two innovative configurations of interconnection networks based on fractal Sierpinski and a hypercube. These are called 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 is considered a great way to reduce costs because it uses fewer nodes and links. The average distance is also shorter, which is better. Despite it having a smaller bisection width and a higher degree than a hypercube by one. The Sierpinski Carpet Topology (SCT) has the advantage of having a high bisection width compared to a hypercube. That is preferable because it places a lower restriction on the difficulty of parallel algorithms. While the drawback of this topology is that it has a diameter and average distance more than a hypercube.

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