While it has been mathematically proven that Projective Splitting (PS) algorithms can converge in parallel and distributed computing settings, to-date, it appears there were no open-source implementations of the full algorithm with asynchronous computing capabilities. This note fills this gap by providing a Julia implementation of the asynchronous PS algorithm of Eckstein and Combettes for solving fully nonsmooth convex optimization problems. Our methodology includes inter-operability with existing packages within the Julia ecosystem, and we also document observations from running this algorithm asynchronously on problems in image processing and machine learning.