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Future space applications will demand for architectures with High Performance Computing (HPC) capabilities. In this scope, on-board computer designers will have to select between different technologies and designs, the most reliable and most efficient ones in terms of performance and power consumption. In this paper, we investigate the behavior of an Image Reconstruction Algorithm on high performance multi-core CPUs and many-core GPUs. It turns out that SAR applications can profit much more from the architecture and the capabilities of many-core GPUs than from modern multi-core CPUs. We give some remarks on how these types of HPC components can be integrated on future space-based on-board computing platforms. Throughout the paper, we illustrate by comparison the advantages and disadvantages of using GPUs over CPUs for SAR Applications. Other than this, we explain the programming and parallelization paradigms applied to the SAR application to increase its performance and efficiency on CPUs and GPUs respectively.