Recently, due to drastically reducing costs of sequencing a human DNA molecule, the demands for next generation DNA sequencing (NGS) has increased significantly. DNA sequencers deliver millions of small fragments (short reads) from random positions of a very large DNA stream. To align these short-reads such that the original DNA sequence is determined, various software tools called short read mappers, such as Burrows BWA, are available. Analyzing the massive quantities of sequenced data produced using these software tools, requires a very long run-time on general-purpose computing systems due to a great computational power it needs. This work proposes some methods to accelerate short read alignment being prototyped on an FPGA. We use a seed and compare architecture based on FM-index method. Also pre-calculated data are used for more performance improvement. A multi-core accelerator based on the proposed methods is implemented on a Xilinx Virtex-6. Our design performs alignment of short reads with length of 75 and up to two mismatches. The proposed parallel architecture performs the short-read mapping up to 41 and 19 times faster than parallel programmed BWA run on eight-core AMD FX9590 and 6-cores Intel Extreme Core i7-5820 k CPUs using 8 and 12 threads.

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