Misale Claudia, Ferrero Giulio, Torquati Massimo, Aldinucci Marco
Computer Science Department, University of Turin, Italy.
School of Life and Health Sciences, University of Turin, Italy.
Biomed Res Int. 2014;2014:539410. doi: 10.1155/2014/539410. Epub 2014 Jul 24.
In this paper, we advocate high-level programming methodology for next generation sequencers (NGS) alignment tools for both productivity and absolute performance. We analyse the problem of parallel alignment and review the parallelisation strategies of the most popular alignment tools, which can all be abstracted to a single parallel paradigm. We compare these tools to their porting onto the FastFlow pattern-based programming framework, which provides programmers with high-level parallel patterns. By using a high-level approach, programmers are liberated from all complex aspects of parallel programming, such as synchronisation protocols, and task scheduling, gaining more possibility for seamless performance tuning. In this work, we show some use cases in which, by using a high-level approach for parallelising NGS tools, it is possible to obtain comparable or even better absolute performance for all used datasets.
在本文中，为了提高生产力和绝对性能，我们倡导针对下一代测序仪（NGS）比对工具采用高级编程方法。我们分析了并行比对问题，并回顾了最流行的比对工具的并行化策略，所有这些策略都可以抽象为单一的并行范式。我们将这些工具与移植到基于FastFlow模式的编程框架上的情况进行比较，该框架为程序员提供了高级并行模式。通过使用高级方法，程序员从并行编程的所有复杂方面（如同步协议和任务调度）中解放出来，获得了更无缝地进行性能调优的可能性。在这项工作中，我们展示了一些用例，其中通过对NGS工具进行并行化的高级方法，对于所有使用的数据集都有可能获得相当甚至更好的绝对性能。
