Parallel Object Compositions for the Search of Sequences DNA Strings in the Construction of Gnomes

Within an environment of parallel objects, an approach of structured parallel programming and the paradigm of the orientation to objects show a programming method based on high level parallel compositions or HLPCs to solve two problems of combinatorial optimization: grouping fragments of DNA sequences and the parallel exhaustive search (PES) of RNA strings that help the sequence and the assembly of DNAs. The pipeline and farm models are shown as HLPCs under the object orientation paradigm and with them it is proposed the creation of a new HLPCs that combines and uses the previous ones to solve the cited problems. Each HLPC proposal contains a set of predefined synchronization constraints between processes, as well as the use of synchronous, asynchronous and asynchronous future modes of communication. This article shows the algorithms that solve the problems, their design and implementation as HLPCs and the performance metrics in their parallel execution using multicores and video accelerator card.