Earticle

Large volumes of short reads of genomic data are generated by high-throughput sequencing instruments. The FASTQ format is widely accepted as the input format of genomic reads and has presented challenges in data storage, management, and transfer. The performance of this type of serial algorithms such as G-SQZ and DSRC is limited by the single processor and the memory in a single computer. Utilizing data parallelism, the circular dual queues of buffers, memory mapping integrated with superblocks, pipeline parallelism with multi threads, and so on, we present the parallel compression and decompression methods for DNA sequence reads in FASTQ format based on the parallel computer architectures of the cluster and the SMP. Experimental results for the parallel DSRC algorithm clearly show the efficiency of using the powerful computing resources from multi computing nodes and multi cores of each node. The speedups vary from 46 to 62 for parallel compression and vary from 40 to 58 for parallel decompression by using 10 nodes of the cluster in Tianhe-1A super computer. Test results on the SMP machine are also pleasant. The methods could be applied to any serial compressing algorithms of DNA sequence reads in FASTQ format only if they have the traits of index and superblocks.