As processors and systems on chip in the embedded world increasingly become multicore, parallel programming remains a difficult, time-consuming and complicated task. End users who are not parallel programming experts have a need to exploit such processors and architectures, using high level programming languages, like Scilab or MATLAB. The ALMA toolset solves this problem: it takes Scilab code as input and produces parallel code for embedded multiprocessor systems on chip, using platform quasi-agnostic optimizations. The platform information is provided by an architecture description language designed for the purpose of a flexible system description as well as simulation. A hierarchical system description in combination with a parameterizable simulation environment allows fine-grained trade-offs between simulation performance and simulation accuracy.