We demonstrate an efficient and accelerated parallel, sparse depth reconstruction framework using compressed sensing (compressed (CS)) approximate computing. Employing data parallelism for rapid image formation, the is reconstructed from sparsely sampled scenes convex optimization. Coupled with faster imaging, this sampling reduces significantly projected laser power in active systems such as l...