The introduction of compressed sensing methods to speed up image acquisition has received great attention in the Magnetic Resonance Imaging (MRI) community. Compressed sensing exploits the compressibility of medical images to reconstruct unaliased images from undersampled data. Moreover, compressed sensing can be synergistically combined with previously introduced acceleration methods such as parallel imaging, which employs arrays of receiver coils to further increase imaging speed. Over the past three years, we have been working on the combination of compressed sensing and parallel imaging, exploiting the idea of joint multicoil sparsity. In this work, we present a summary of our image acquisition and reconstruction methods for the combination of compressed sensing and parallel imaging, and describe applications to cardiac and body dynamic MRI.