The evolution of the field of programming traditionally trades performance for more powerful abstractions that are able to simplify the programmer’s work. It is possible to observe the effects of this evolution on the parallel programming area. Typically parallel programming focuses on high performance based on the procedural paradigm to achieve the highest possible throughput, but determining the point in which one should trade performance for more powerful abstractions remains an open problem. With the advent of new system level tools and libraries that deliver greater performance without programmer’s intervention, the belief that the application programmer should optimize communication code starts to be challenged. As the growing demand for large scale parallel solutions becomes noticeable, problems like code complexity, design and modeling power, maintainability, faster development, greater reliability and reuse, are expected to take part on the decision of which approach to use. In the present work, we investigate the use of higher-level abstraction layers that could provide many benefits for the parallel application developer. We argue that the use of interpreted languages may aid the abstraction of the processor architecture providing an opportunity to optimize the virtual machines without affecting the user’s application code.