The high resolution imaging capability of Synthetic Aperture Radar (SAR) is largely unaffected by atmospheric conditions and has proven to be an indispensable asset in a variety of military and civilian applications. Application of SAR methodology for real-time imaging however carries with it the large computational complexity and storage requirements of the image-forming algorithms. Recently however, the rapidly diminishing cost of computing hardware and the related ascent of cluster-based computing, has made parallelization of these algorithms an appealing area of investigation. This paper describes a parallel SAR processor developed at MIT Lincoln Laboratory. Several novel technologies were employed in it's implementation, including pMatlab which is a parallel extension of standard Matlab that is also being developed at MIT Lincoln Laboratory. These technologies will be described later in the document. We begin with a brief description of the basic SAR algorithm.