Parallel programming with pictures is a Snap!

This ubiquitous parallelism in hardware presents a major challenge: the difficulty in easily extracting parallel performance via current software abstractions. Consequently, this paper presents an approach that reduces the learning curve to parallel programming by introducing such concepts into a visual (but currently sequential) programming language called Snap!, which was inspired by MIT's Scratch project. Furthermore, our proposed visual abstractions can automatically generate parallel code for the end user to run in parallel on a variety of platforms from personal computing devices to supercomputers. Ultimately, this work seeks to increase parallel programming literacy so that users, whether novice or experienced, may leverage a world of ubiquitous parallelism to enhance productivity in all walks of life, including the sciences, engineering, commerce, and liberal arts.