Design and Implementation of high-performance sequence analysis environment using GPGPU

随着高通量测序平台的出现，DNA测序的实验成本和时间成本都大大降低。这使得产生大量DNA数据变得容易。因此，分析庞大的序列数据库已成为寻找高效解决方案的下一个目标。为了克服这个问题，我们应用通用计算图形处理单元（GPGPU）的序列分析。在GPGPU上实现了Smith-Waterman算法等多种算法。与基于CPU的程序相比，基于GPU的程序表现出更高的性能。

Since the emergence of high-throughput sequencing platform, the cost for both experimental and time were much reduced for DNA sequencing. This makes easy to produce enormous amount of DNA data. As the result, analyzing huge sequence database has become a next target to find an e & cient solution. To overcome this problem, we applied General Purpose computation on Graphic Processing Unit(GPGPU) for sequence analysis. We implemented several algorithms including Smith-Waterman algorithm based on GPGPU. The GPU-based programs showed higher performance compared to CPU-based ones.