A data-driven workflow language for grids based on array programming principles

Different scientific workflow languages have been developed to help programmers in designing complex data analysis procedures. However, little effort has been invested in comparing and finding a common root for existing approaches. This work is motivated by the search for a scientific workflow language which coherently integrates different aspects of distributed computing. The language proposed is data-driven for easing the expression of parallel flows. It leverages array programming principles to ease data-intensive applications design. It provides a rich set of control structures and iteration strategies while avoiding unnecessary programming constructs. It allows programmers to express a wide set of applications in a compact framework.