The article outlines a contemporary method for creating software for multi-processor computers. It describes the identification of parallelizable sequential code structures. Three structures were found and then carefully examined. The algorithms used to determine whether or not certain parts of code may be parallelized result from static analysis. The techniques demonstrate how, if possible, existing sequential structures might be transformed into parallel-running programs. A dynamic evaluation is also a part of our process, and it can be used to assess the efficiency of the parallel programs that are developed. As a tool for sequential programs, the algorithms have been implemented in C#. All proposed methods were discussed using a common benchmark.

The work presented in the paper concerns a very important problem of searching for string alignments. The authors show that the problem of a genome pattern alignment could be interpreted and defined as a measuring task, where the distance between two (or more) patterns is investigated. The problem originates from modern computation biology. Hardware-based implementations have been driving out software solutions in the field recently. The complex programmable devices have become very commonly applied. The paper introduces a new, optimized approach based on the Smith-Waterman dynamic programming algorithm. The original algorithm is modified in order to simplify data-path processing and take advantage of the properties offered by FPGA devices. The results obtained with the proposed methodology allow to reduce the size of the functional block and radically speed up the processing time. This approach is very competitive compared with other related works.