The use of high performance computing has been gaining more and more followers in the different branches of Science and Engineering given the potential offered to deal with complex and big problems, and the increasing economic facilities to configure some kind of parallel machine. However, the parallel programming paradigm involves additional aspects to the merely functional which could provoke different kinds of bottlenecks in the performance of the applications. Such difficulties may represent critical obstacles specially for the non-expert users. In this paper we present an environment to provide general support for the automatic development and tuning of parallel applications. The environment provides an interface to guide the user in the specification of the problem and the solution, which makes transparent the process of code generation and instrumentation. Because the parallelization of any problem/solution is hard to generalize, the environment tackles different classes of problems. In this article, we introduce the class of Parallel Genetic Algorithms.Sociedad Argentina de Informática e Investigación Operativa