Memory affinity in multi-threading: the Bowtie2 case study
Claudia Misale, Marco Aldinucci, Massimo Torquati · 2013
The diffusion of the Next Generation Sequencing (NGS) has increased the amount of data obtainable by genomic experiments. From a DNA sample a NGS run is able to produce millions of short sequences (called reads), which should be mapped into a reference genome. In this paper, we analyse the performance of Bowtie2, a fast and popular DNA mapping tool. Bowtie2 exhibits a multithreading implementation on top of pthreads, spin-locks and SSE2 SIMD extension. From parallel computing viewpoint, is a paradigmatic example of a software requiring to address three fundamental problems in shared-memory programming for cache-coherent multi-core platforms: synchronisation efficiency at very fine grain (due to short reads), load-balancing (due to long reads), and efficient usage of memory subsystem (due to SSE2 memory pressure). We compare the original implementation against an alternative implementation on top of the FastFlow pattern-based programming framework. The proposed design exploits the high-level farm pattern of FastFlow, which is implemented top of nonblocking multi-threading and lockless (CAS-free) queues, and provides the programmer with high-level mechanism to tune task scheduling to achieve both load-balancing and memory affinity. The proposed design, despite the high-level design, is always faster and more scalable with respect to the original one. The design of both original and alternative version will be presented along with their experimental evaluation on real-world data sets.