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Optimizing Data Intensive GPGPU Computations for DNA Sequence Alignment.
Parallel Computing ( IF 1.4 ) Pub Date : 2009-08-01 , DOI: 10.1016/j.parco.2009.05.002
Cole Trapnell 1 , Michael C Schatz
Affiliation  

MUMmerGPU uses highly-parallel commodity graphics processing units (GPU) to accelerate the data-intensive computation of aligning next generation DNA sequence data to a reference sequence for use in diverse applications such as disease genotyping and personal genomics. MUMmerGPU 2.0 features a new stackless depth-first-search print kernel and is 13× faster than the serial CPU version of the alignment code and nearly 4× faster in total computation time than MUMmerGPU 1.0. We exhaustively examined 128 GPU data layout configurations to improve register footprint and running time and conclude higher occupancy has greater impact than reduced latency. MUMmerGPU is available open-source at http://mummergpu.sourceforge.net.

中文翻译:

为 DNA 序列比对优化数据密集型 GPGPU 计算。

MUMmerGPU 使用高度并行的商品图形处理单元 (GPU) 来加速将下一代 DNA 序列数据与参考序列对齐的数据密集型计算,以用于疾病基因分型和个人基因组学等多种应用。MUMmerGPU 2.0 具有新的无堆栈深度优先搜索打印内核,比对齐代码的串行 CPU 版本快 13 倍,总计算时间比 MUMmerGPU 1.0 快近 4 倍。我们详尽地检查了 128 个 GPU 数据布局配置,以改善寄存器占用空间和运行时间,并得出结论,更高的占用率比减少延迟的影响更大。MUMmerGPU 可在 http://mummergpu.sourceforge.net 上开源。
更新日期:2019-11-01
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