An important challenge in parallel computing is the mapping of parallel algorithms to parallel computing platforms. This requires several activities such as the analysis of the parallel algorithm, the definition of the logical configuration of the platform and the implementation and deployment of the algorithm to the computing platform. However, in current parallel computing approaches very often only conceptual and idiosyncratic models are used which fall short in supporting the communication and analysis of the design decisions. In this article, we present ParDSL, a domain-specific language framework for providing explicit models to support the activities for mapping parallel algorithms to parallel computing platforms. The language framework includes four coherent set of domain-specific languages each of which focuses on an activity of the mapping process. We use the domain-specific languages for modeling the design as well as for generating the required platform-specific models and the code of the selected parallel algorithm. In addition to the languages, a library is defined to support systematic reuse. We discuss the overall architecture of the language framework, the separate DSLs, the corresponding model transformations and the toolset. The framework is illustrated for four different parallel computing algorithms.